Along with the presence of the CHIME community, ViVE offers an opportunity for more than 8,000 health leaders—including a sizable number of C-suite executives—to engage in operational and “from the heart” exchanges shaping a long-awaited sector transformation – from fragmented to fluid.

Nashville, celebrated nationally as Music City and an epicenter of health innovation, may play a Swiss-like role in the much-needed shift that must happen sooner rather than later. It is a city of possibilities and a health community built around purpose, entrepreneurial energy, and a collaborative mindset.  If changes in the health system are remotely possible, it is because the town’s ” vibe ” is inclusive and built on realizing dreams and hopes.

At ViVE, the conversation around Artificial Intelligence (AI) has evolved dramatically during the past four meetings. What was once speculative hocus-pocus is now embraced as essential and operational. AI is often mischaracterized as “artificial intelligence.” The correct term that should be applied to the reality of its integration in the workflow is “augmented implementation,” a tool that amplifies human capabilities rather than replacing them. This distinction is key to understanding that AI fits into the health ecosystem’s future, where precision, trust, and efficiency converge.

A recent report from MarketsandMarkets states that the AI in healthcare market size is estimated to surge from USD 20.9 billion in 2024 to USD 148.4 billion by 2029.

The Evolution from Theory to Practice

Reflecting on previous ViVE conferences, the discussion around AI was theoretical and focused on potential applications, ethical considerations, and integration challenges. At ViVE 2025, that narrative continues to head in a focused endpoint direction. AI advancements through ChatGPT and large language models (LLMs) are a given asset embedded in health workflow.

Sessions now showcase real-world applications, from AI-driven clinical decision support to streamlined administrative processes and enhanced patient engagement. The focus is no longer on possibility but on action—how organizations can effectively harness AI to improve outcomes and efficiency in care and cost.

Addressing Cost Inefficiencies and Workflow Optimization

The buzz on the stage and exhibit hall is a common message. One of the most critical aspects of AI integration into health is its potential to address repetitive actions and overcome systemic challenges. Leveraging AI and data analytics, health professionals can identify disease and diagnostic possibilities that escape their training eye and imagination, reduce cost inefficiencies, and optimize health system workflows – from procedure and patient scheduling to finding correct billing codes.

AI-driven insights enable a more equitable distribution of resources, ensuring that underserved populations receive the care they need when needed. Moreover, automating administrative tasks should free up time for clinicians, reducing burnout and allowing them to focus on patient-centered care.

Major Players Accelerate AI Adoption

Industry giants like Amazon, Epic, Microsoft, and Oracle are propelling the rapid integration of AI into health care. These companies are not just developing AI tools that others use as platforms but fostering collaborations to ensure seamless integration within existing health infrastructures.

Amazon: With a strategic investment of up to $4 billion in Anthropic, Amazon is expanding its generative AI capabilities within Amazon Web Services (AWS). Its initiative aims to equip health organizations with advanced AI-driven tools to enhance patient care and operational efficiency.

Epic: Beyond its Microsoft partnership, Epic continues to lead in AI integration, ensuring providers can access cutting-edge tools to improve clinical decision-making and patient engagement.

Microsoft: To deepen collaboration with Epic, Microsoft has embedded its Azure OpenAI Service into the Epic electronic health record (EHR) software. This integration enables generative AI tools to optimize clinical workflows, reduce administrative burdens, and enhance decision-making.

Oracle: Recognizing AI transformative potential, Oracle has introduced generative AI tools within its EHR systems. These tools automate routine tasks, allowing health professionals to devote more time to patient care.

Entrepreneurial Companies Driving Change

ViVE is not only about the industry’s most prominent health IT players coming together under one roof but also a platform where entrepreneurial companies push the industry forward. Smaller AI-driven start-ups and health tech service providers function as a pipeline for innovation, capturing media attention and influencing companies’ mergers and acquisitions (M&A) and investment strategies.

Here are three companies that started small and have become sector change agents:  

Abridge: In February 2025, Abridge raised a $250 million Series D investment that now has the company valued at $2.5 billion. This funding supports deploying their AI-driven clinical documentation platform across more than 100 health systems, including prominent institutions like Duke Health, Johns Hopkins, Mayo Clinic, and UNC Health. The investment also fuels the development of its new Contextual Reasoning Engine, designed to produce billable clinical notes at the point of care, streamlining workflows and reducing administrative burdens.

Cohere Health: Cohere Health is a clinical intelligence company transforming the prior authorization process. By leveraging artificial intelligence, Cohere streamlines administrative paperwork, expediting patient access to necessary care. Their mission is to simplify health by fostering collaboration among patients, physicians, and health plans, ensuring the proper care is delivered promptly and effectively.

Qventus: In January 2024, Qventus announced a $105 million Series D investment led by powerhouse KKR, with participation from Bessemer Venture Partners and investors such as Northwestern Medicine, HonorHealth and Allina Health. This funding aims to enhance Qventus AI-based care automation software, optimizing hospital operations by predicting patient flow and reducing inefficiencies that impact revenues.

These entrepreneurial players—now operating at scale and resourced—challenge industry norms and encourage the mega information players to rethink how their platforms can be the “Intel-inside” service provider systems.

Collaboration is the Catalyst for Innovation

The true power of AI in health emerges from collaboration. Collaboration among technology leaders and health institutions drives innovation, ensuring AI solutions address real-world challenges. That has been a clear message during ViVE 2025.

The Microsoft-Epic collaboration is a driver in integrating AI within EHRs to analyze vast datasets, providing clinicians with actionable insights that improve patient care. Similarly, the Amazon investment in Anthropic is advancing generative AI to enhance health operations. These alliances demonstrate how combining technological expertise with health knowledge leads to breakthrough solutions.

ViVE has become a welcoming platform for fostering these collaborations, bringing health and technology leaders together to discuss AI’s practical applications. The 2025 meeting agenda reflects this focus, offering hands-on sessions that provide attendees with tangible AI implementation strategies and case studies.

The Future of Augmented Implementation in Health

The “augmented implementation” concept is more relevant than ever as we stand at the intersection of technology and health – and a new Administration pushing AI as an elixir for what ails the industry and US global competitiveness. While many wonder whether AI will replace human expertise, there is little debate about whether it will enable more transparent decision-making and efficient care delivery.

The shift from theoretical discussion to practical application has been faster than expected, fueled by collaboration, innovation, and a shared hope for improved patient care. The AI footprint in health will continue to expand, and its success will depend on maintaining a balance between technological advancement and human-centered care.

ViVE is a time capsule of obstacles, anxieties, and health system progress integrated with our combined wisdom into practice. Conversations continue to evolve, collaborations deepen, and applications become more practical. As we continue to embrace “augmented implementation,” the future of health is encouraging—where technology amplifies human potential and delivers unparalleled value to patients and providers alike. ViVE continues to be a place for open, candid exchange.

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The LLM Cancer Mentor App is a revolutionary tool for cancer patients, caregivers, and physicians. It’s like having a WAZE for navigating the complex cancer diagnostic and care journey.  No longer do patients have to wait for their next appointment to get answers to their questions. They now have a high-level concierge coach available 24/7, ushering in what innovation theorist John Nosta calls ‘The Age of Cognition ‘.

“Perhaps one of the most complex things about oncology is complexity itself. From clinical knowledge and understanding to articulating difficult concepts with patients. Part of what large language models (LLMs) offer is the ability to provide a cognitive assistant that serves up information that is organized and important, and delivers it away that is more relevant and understandable,” said Nosta to Medika Life. “This is perhaps most important with patients who often find the complexity of oncology to be one of the worst toxicities of both therapy and disease,” he added.

ChatGPT Controversial Perhaps, But Patient Preferred

Last year, a controversial JAMA study suggested patients often preferred ChatGPT tools to physician conversation.  A chatbot generated quality and empathetic responses to patient questions online in this cross-sectional study.  While physicians doubted the study’s design, it was evident from data and public conversation that technology available in real-time answering patients’ pressing clinical and emotional needs was sought and welcomed. Even Eric Topol, MD, a long-time AI advocate reports that augmented information can potentially save lives.

Now, the large language model (LLM) called Dave AI was created by Belong.Life increases patient engagement and provides personalized support.  Medika Life spoke with one of the world’s foremost digital health leaders, who marshaled the potential of technology and tapped medical and drug development experts and patient feedback systems to develop AI, ChatGPT, and LLMs tools to support cancer patient advocacy and innovation.  Eliran Malki, the co-founder and CEO of Belong.Life, is a proven entrepreneur and business leader who has founded, financed, and led several successful companies, including More IT Resources Ltd., acquired by Dell-EMC, Veracity Ltd., acquired by EMET, and others.  Together with Co-Founder Irad Deutsch, they launched Belong.Life almost a decade ago. Today, the company serves patients around the globe.

Malki’s blueprint for success isn’t a closely guarded secret – he consistently creates tech platforms that provide easily accessible, practical, and consistent value to users.  Belong.Life is a multilingual HIPAA, GDPR, and ISO-compliant community combining science, service, and solutions to unite patients, payors, product innovators, policymakers, and provers. It demonstrates that the LLMs can provide patients with the support essential to their cancer care journey – augmented information on-demand.

[The  Dave Cancer Mentor app can be downloaded here.]

Dave AI Created to Improve the Patient Journey

Eliran Malki, Co-Founder and CEO, Belong.Life: Dave AI was among the reasons we launched Belong Life – to improve people’s care journey and, ultimately, possibilities for outcome success. We trained this unique LLM (large language model) on an extensive knowledge base of 80 million discussions between patients and physicians. Over eight years, it’s accumulated knowledge of numerous physicians with 100,000 patients discussing the Belong Life app. The training process involved anonymizing and aggregating data to ensure patient privacy and security.

Gil Bashe, Editor-in-Chief, Medika Life: Incredible, eight years and 80 million discussions. How did you distill millions of exchanges and infuse them into Dave AI’s mind? Could you explain the process?

How Does the Dave AI LLM Work?

Malki: We started about six to seven years ago. There are a lot of questions that sometimes people lack the confidence to ask their physicians. People too often have only 10 or a maximum of 20 minutes with their provider. Patients want to ask the top two to three pressing questions, but you don’t do that if you are shy or intimidated to raise a topic.  At the same time, physicians want nothing more than help. Dave AI is a bridge between patients and their physicians – it helps prepare and strengthen the person-to-person relationship.

Here is a video summary of how Dave AI works:

With Dave AI, you can ask about treatment options, potential therapy side effects, clinical trials, or even managing your symptoms – pain, sexual function, or personal care. You’ll receive a supportive, comprehensive answer that covers all aspects of your query. We want to give the best services to patients at all hours, day and night, to educate and empower. Dave AI enables us to support millions of patients and prepare them to use their time with physicians productively. Everyone can get maximum support immediately. It’s suitable for payors, good for providers, and, most importantly, for patients.  It’s a model that combines the best of medicine, patient-physician relationships, and technology.

Dave AI Access for Everyone was Important to Belong.Life

Bashe: I have a question about cost. I understand there’s a free app download on any platform at no cost to the patient.

Malki: Yes, free of charge. We created three service levels to ensure this LLM technology is accessible to all.  The new Dave AI Mentor app is a free zone with premium services. The Dave AI Mentor answers questions and works with patients as a navigator along their cancer journey. It will ask about your upcoming tests; it will help people keep a diet and exercise regimen on track. Depending on your journey, it will be a health case manager and a constant ally. Dave AI will call you and answer questions that you ask, and it will also ask you questions to help model engagement. It’s similar to a coach,

We’re doing many things with hospitals, physicians and insurers that now cost $14.99 monthly. If you are an insurer, you can offer a patient, Dave AI, as a mentor or a case manager who’s available 24/7 and provides support with education and information for $150 per year. It’s the same for hospitals.

Bashe: So, are there different levels of Dave AI services to provide for people with varied economic and information needs?

Malki: Correct. There is a free version, a Pro version, and a Power Plus version. Everyone gets a seven-day trial to use everything. Most users renew. We start billing in January. If people don’t want to pay for an entire year midpoint in the cycle, they can use the free version first.  Many patients prefer the yearly subscription at $120 to $179, which offers unlimited access and added services.

Bashe: I’m curious – do you white-label Dave AI for hospital systems? For example, would it be possible for centers of excellence such as Memorial Sloan Kettering or Hackensack Meridian to secure a branded version of Dave AI catering to their patient needs?

Malki: Yes.  This is central to our service and patient care efforts. We are a technology company.  But we are, first and foremost, a patient-care service platform.  We want people to use and access the best of technology to improve their health.

Bashe: I wanted some background about basic free Dave AI. Now, some people are economically hard-pressed at the same time. Though $149 per year is not a lot when your life may be on the line, you have ensured that there is access to all, regardless of economics. How do Dave AI, Dave AI Pro, and Dave AI Pro Plus differ?

Imagine an Interactive Cancer Expert Available 24/7

Belong.Life’s new oncology AI mentor, Dave, provides accurate, personalized and accessible information instantaneously for people navigating the cancer journey. Dave is available on Belong’s Beating Cancer Together app.

Malki: Some people post 2,000 questions – some read  more than 5,000 posts.  Access to Dave AI for all is essential.  At the same time, someone speaking with an expert resource for 2,000 posts and chats should become a subscriber to the service because it is an incredible investment for us to create, operate, and continuously perfect the system.

Bashe: How many questions can you ask from the free Dave AI before going from Dave AI Pro to Dave AI Plus?

Malki: The free version is limited to 10 questions; the user must wait a week afterward—10 for the first week and then five per week. Many patients value the service, realize its immediate benefits, and are willing to pay. Taking a photo of a clinical document – uploading diagnostic test results – and understanding the document while you are still in the MRI waiting room is an incredible benefit, rather than waiting before you see the physician to discuss the written report. It is of considerable value that Dave AI can read, analyze, and provide feedback almost immediately.   

Scheduling a meeting with a physician is time-consuming and emotionally consuming. You call to wait days or weeks – a day feels like a lifetime.  Sometimes, you need questions answered immediately, seek elaboration, and say, “Please explain again; I didn’t understand that.” So, Dave AI is crucial for patients’ care and mental well-being.

Bashe: With Dave AI Pro Plus, people can ask as many questions as possible?

Malki: Yes.  As many as you want, all the time, 24/7.

How Does Smart Tech Get Smarter?

Bashe: I wanted to get a sense of the evolution of Dave AI. So, I understand that Dave AI is very smart today. How does Dave AI maintain that high level of intelligence week after week?

Malki:  Great question. This is a unique and critical accuracy feature that we patented.  It’s known as the Arch Methodology. The Arch stands for Accuracy, Responsibility, Compliance, and Hallucination-free. AI must always answer accurately; if Dave AI doesn’t know the answer, he can’t invent it. He will say, “I cannot answer.” Telling the AI what not to answer is as important as telling them what and how to respond.

We have several LLM multiplexers. [AS1] This is also one of our patents. All information goes through feedback classification, sentiment analysis, an RLHF Engine (Reinforcement Learning from Human Feedback), and a machine learning approach combining human guidance to train the AI tool..

Every change also goes through several tests and the automated ARCH-validated protocols.

Speed Accelerated for Clinical Trial Inclusion

We have been offering a clinical trial recruitment service for patients for the past six years. The average time for matching a patient to a clinical trial before  September 2023 was 5.4 days from when the patient started speaking to us.. Once we launched and added another LLM called Tara to our clinical trials matching program, the median connect time was 9 minutes, and the average was 2 ½ hours. The patient also can upload their documents, and the system will do all the work.

Eliminating the Tension of Waiting for Answers

The BelongAI Dave – Cancer Mentor app provides 24/7 accurate, personalized, and proactive support and information for people navigating the cancer journey.

Bashe: If you have 15,000 patients, those are 15,000 people who don’t have to wait 5.4 days.  There is also the issue of reducing anxiety levels for someone who has just been diagnosed with cancer. How do they take control of a situation when their life is out of control? They collect information and act on it. If they’re lingering in the trial search environment for five days or three days, that increases their anxiety levels. If they search for only three hours, that reduces their anxiety level.

It’s a little bit like having an interview for a job, and you’re waiting 5-6 days to find out if you got the job, or if they call you back in 3 hours and you got the job, what’s your anxiety level while waiting to hear about the job? It’s off the charts. By day 5 ½, you’re wondering why you didn’t get it.

Unintended cruelty is baked into the clinical trial enrollment and care system, which keeps people hanging. Dave AI and Tara AI eliminate that factor.

Malki: It gives them hope. The patient asked for and got information relevant to the clinical trial, whereas people generally wait till a physician tells them.

Bashe: The reality is that Dave AI hones the process. The patient isn’t necessarily going to run off and enlist in a trial; they’ll say to their doctor, “Look, I’ve gotten three possible trials from this database that fit my profile; what do you think?” It’s not an exclusion of the doctor; it’s accelerating the doctor’s ability to look over information and reply. Technology is not a replacement for a doctor; you understand that democratizing decision-making accelerates your enterprise’s decision-making pace. Same with the doctor.

The doctor, who’s cognitively sharp and psychologically sturdy, now has a patient who is much more engaged with the system. It’s not that Dave AI is the only trusted source; it’s that Dave AI is accelerating the patient’s ability to engage their doctor. The doctor can speak to the patient for five minutes and say, “I looked over your stuff; I think these are three good choices; I would go with this one as the priority, and tell me when you’ve enrolled.” The doctor never loses control over the patient. Oncologists want patients who remain alive.

I have a key question I will make sure to grab: How does Dave AI today get smarter tomorrow? What’s the rate of ability to make Dave smarter?

Malki: There are several factors involved in being smart in AI.. If you want chats, you will need Open AI, Gemini , or something like that, as you see in a mixed style, or Falcon, which is among the best. There are top five in the world as generative AI, and we’re just using three of them, running them on our classifications and our data – there’s no one in the market with our data. No one has the same physician-patient discussion database.

What makes us much better is that we added data from Dave AI’s patient exchanges. We deploy these patient discussions, remarks, and feedback. Dave AI is continuously improving.

Layers and Levels to Ensure Accuracy

Malki: 

We took the platform of AIand built three levels of what we call autonomous AI. Level 1 is controlled;. This is the easiest step forward for pharma, the FDA, and regulations. Gen 2 – this information is 100% accurate because the first one is pre-defined and pre-scripted; I have the approved answers, and the physician sends the second one.

Level 2 is a generative AI agent for specific documents, only . That’s amazing for hospitals, especially for logistical or administrative questions. Information that can lower stress and free the professional team.

Level 3 is a fully automated conversation with AI.  This is a Highly scaleable and valuable solutions

Bashe:  We’ve entered the cognitive age. With large language models, you’re in conversation. It understands that there’s a conversational tone to every exchange. You can use the LLM for half an hour or 40 minutes until you feel you’ve exhausted your train of thought.

Malki: Every payor, every provider, and every patient needs access to these platforms  as triage services to lower stress – the burnout level for professionals and increase the value to patients.  To review for Medika readers, here are the three Dave AI service options:

Dave Pro:

• Proactive check-ins with users about previously discussed concerns, scheduled treatments, and more.
• Precise, comprehensive, and empathetic answers to cancer-related questions and challenges.
• Document analysis and explanations of clinical terminology in easy-to-understand language.
• Access a personalized, continuously updated library of information on treatment options, side effects, and emotional well-being.
• Medication management, appointment notifications, and reminders.

Dave Pro Plus offers Dave Pro features through Tara, Belong.Life AI-powered assistant that matches patients to clinical trials based on their unique medical situations and locations. Through ongoing searches, Tara identifies new treatments and clinical trials and shares easy-to-read monthly summaries to update patients on treatment possibilities.

Dave Community allows patients to interact with Dave in a public forum, enabling users to understand other patients’ challenges and interactions with Dave.  

So, what do doctors think about Dave AI?  

We spoke with Ilya Iofin, MD, the Chief of Orthopaedic Oncology Service at Mount Sinai Hospital.

“Thank you, Gil. I first started working with Belong in 2017 or 2018.  Dave AI gives accessibility because you have this additional resource where anyone can understand the answer. AI is trained and based on what physicians say. You can use medical lingo and confuse everybody or try to explain it in terms that a reasonably intelligent person can understand. I think AI will do the same thing if AI learns from physicians who can get their thoughts and information across in reasonable human speech.

“Specialized medicine, especially oncology, differs from any other field. I’m a physician. If I talk to a car mechanic, he needs to explain, in terms I understand, how a car and engine work. Or I’ll just be as confused as the guy who knows nothing about cars. That’s the benefit of this LLM for people confronting cancer.”

Welcome to the Age of Cognition

Dave AI and LLM enable patients to navigate the complexity of medical care – from diagnosis to treatment to being in dialogue with their care team – which are critical to outcomes.  Malki and his team of engineers, physicians, medical professionals, and patient allies are showing us that LLM is not space-age technology.  LLM enables people diagnosed with cancer to overcome one of the disease’s biggest challenges: learning a language they never thought or wanted to understand.

Patient Advisory

Medika Life has provided this material for your information. We note that this platform and information provided are not intended to substitute for the medical expertise and advice of your health care provider(s). We encourage readers to discuss any clinical decisions on treatment or care with a health care provider. The mention of any product, service, or therapy is not an endorsement by Medika Life.

The post LLM Cancer Mentor “Dave AI” Offers WAZE-like 24/7 Personalized Support, Making it a Game-Changer in Patient Care appeared first on Medika Life.

I recently thought about my day as an oncologist and was surprised at how artificial intelligence (AI) infiltrates every corner of my specialty, breast cancer.

Screening mammograms? Check. Helping read the pathology report? Check again. Helping predict what drug is best for breast cancer treatment? Yup, AI can help.

First, a sobering observation from the late Stephen Hawking:

“The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”

AI and Breast Cancer

But what about artificial intelligence in healthcare? AI is involved in the care of the vast majority of my patients.

Today, I want to share how AI is revolutionizing the practice of cancer medicine. We’ll look at the following examples:

• Breast imaging and artificial intelligence
• Breast pathology and artificial intelligence
• Breast cancer risk prediction

Artificial Intelligence (AI) has tremendous potential to advance clinical practice and patient care delivery.

Overview

Cancer remains among our most challenging health issues, affecting millions worldwide.

Despite significant advances in medical science and technology, the fight against cancer remains an uphill battle. However, in recent years, a formidable ally has emerged in this battle:

Artificial Intelligence (AI). AI is rapidly becoming a game-changer in cancer prediction, diagnosis, and treatment.

In this essay, we will explore the profound impact of AI in unraveling the secrets of cancer, revolutionizing our approach to its detection and management.

Medical Information Volume is Exploding

Artificial intelligence to improve healthcare delivery has arrived. AI is involved in various aspects of my patients’ care.

And just in time. There has been an exponential increase in the medical knowledge needed to guide management for my patients.

The numbers for medical information are breathtaking. Dr. Peter Densen offered these staggering estimates:

• In 1980, medical knowledge doubled every seven years.
• In 2010, the doubling period was 3.5 years.
• In 2020, medical knowledge doubled every 73 days.

Real-World Implications of the Knowledge Explosion

Let’s translate that knowledge doubling time into the life of a medical trainee. What medical students learn in their first three years nowadays would be only six percent of known medical information at graduation.

Sisyphus (or Sisyphos) is a figure from Greek mythology. This Corinthian king gained infamy for his trickery and fierce intelligence.

But his greatest feat? Cheating death and Hades. Not once, but twice. Sisyphus lived up to Homer’s description of him as “the most cunning of men.” (Iliad, 6:153).

However, Corinth’s first king ultimately got his comeuppance when Zeus dealt him the eternal punishment of forever rolling a boulder up a hill in the depths of Hades.

If you practice medicine, you may relate to Sisyphus’ challenge.

The Cancer Conundrum

Cancer is a complex group of diseases characterized by uncontrolled cell growth and the potential to spread to other parts of the body.

Its complexity stems from the fact that there are over 100 different types of cancer, each with its unique behavior, genetic mutations, and treatment challenges.

Traditional cancer detection and treatment approaches have relied heavily on human expertise, limited by human error, subjectivity, and the inability to process vast amounts of data quickly.

AI, on the other hand, offers a new paradigm for understanding and combating cancer. It excels at handling vast datasets, identifying subtle patterns, and making predictions based on data-driven insights.

By leveraging AI, we can delve deeper into the mysteries of cancer, uncovering hidden patterns and gaining a more comprehensive understanding of its underlying mechanisms.

AI in Early Detection

Early detection is often the key to successful cancer treatment. The earlier the cancer is diagnosed, the higher the chances of effective intervention and survival.

AI-powered tools have proven to be invaluable in this regard.

For instance, machine learning algorithms can analyze medical images such as X-rays, MRIs, and CT scans with remarkable precision, detecting abnormalities that might elude even the most skilled human radiologists.

One noteworthy example is the application of deep learning algorithms in breast cancer detection. This is the AI application I encounter most frequently.

Mammography is a common screening tool for breast cancer, but it can produce false positives and negatives.

AI models trained on vast datasets can improve mammogram interpretation accuracy, reducing unnecessary biopsies and ensuring that potential cancers are not missed.

If you read your mammogram report, there is a good chance that the second reader was a robot.

AI and Breast Cancer Screening

Retrospective studies have shown promising results using artificial intelligence to improve mammography screening accuracy and reduce screen-reading workload.

But what about higher-level evidence, such as a randomized trial? An August 2023 research study offers proof of AI’s value.

Swedish researchers assessed the clinical safety of an AI-supported screen-mammogram reading protocol compared with standard screen reading by radiologists following mammography.

As reported in the Lancet Oncology, here are the results:

AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload.

The study authors concluded that AI for mammography screening is safe.

Moreover, AI can process a patient’s medical history, genetic information, and other clinical data to assess their risk of developing cancer.

By identifying high-risk individuals, AI can enable healthcare providers to implement proactive screening and preventive measures, potentially saving lives.

AI to Analyze Cancer Cell Signatures

Understanding a breast cancer’s personality or signature is important before recommending treatment.

The first thing I do when I see a new patient with breast cancer is to look at the pathology report, a description of the cancer cells, and some features driving their behavior.

For example, most breast cancers are driven by estrogen and progesterone. We call them estrogen- and progesterone-receptor-positive (ER/PR +).

When these hormones fuel breast cancer cells, we can dramatically drop the available hormone levels. Alternatively, we might use a drug that clogs up the cancer cell receptors that receive the hormone growth signal.

HER2-positive breast cancer is a breast cancer that tests positive for a protein called human epidermal growth factor receptor 2 (HER2). This protein promotes cancer cell growth.

In approximately one of every five breast cancers, the cancer cells have extra copies of the gene that makes the HER2 protein. HER2-positive breast cancers tend to be more aggressive than other breast cancer types.

Human epidermal growth factor receptor 2 (HER2) protein expression is critical for therapeutic decision-making in breast cancer.

Treatments that specifically target HER2 are very effective. These treatments are so effective that the prognosis for HER2-positive breast cancer can be remarkably good.

(On a side note, two weeks ago, at a breast cancer thought leader conference on the Big Island of Hawaii, I sat next to one of the primary creators of the primary drug that targets Her-2. A fan-boy moment for this clinician.)

AI to Determine HER-2 Status

The most common HER2 scoring approach (immunohistochemistry or IHC) suffers from poor interobserver concordance.

Artificial intelligence (AI) may optimize this scoring regarding standardization, accuracy, and efficiency.

Researchers recently reported using an AI-based HER2 IHC quantifier software to support pathologists in standardized breast cancer assessment. They gathered validation specimens from four institutions and five scanners.

As published in the Journal of Clinical Oncology, here are the promising results:

AI software showed quite high agreement when discriminating HER2-neg from HER2-low/positive cases and general HER2 scoring. AI use also appeared to cut HER-2 evaluation time by nearly half.

A separate study showed significant improvement in inter- and intraobserver agreement when the computer-aided reading mode was used to evaluate preselected image fields.

These results demonstrate AI solutions’ potential to increase the consistency and efficiency of HER2 scoring and ultimately improve patient outcomes.

Personalized Treatment with AI

Cancer is not a one-size-fits-all disease. Each patient’s cancer is unique, driven by specific genetic mutations and molecular characteristics.

AI can tailor treatment plans to individual patients, optimizing therapeutic outcomes.

One of the most promising applications of AI in cancer treatment is in the field of precision medicine. By analyzing a patient’s genetic profile, AI algorithms can identify targeted therapies that are most likely effective.

This approach minimizes broad-spectrum treatments like chemotherapy, which can have debilitating side effects, and instead focuses on treatments that specifically target the cancer’s vulnerabilities.

Furthermore, AI can continuously analyze a patient’s response to treatment, adjusting the therapy regimen in real time based on the evolving nature of the cancer.

This dynamic approach enhances the chances of treatment success while minimizing the adverse effects on the patient’s overall health.

Personalized Treatment with AI: Potential

Earlier this year, I saw this interesting headline: “New AI tool could help doctors better personalize breast cancer treatment.”

Here’s the backstory. University of Waterloo (Ontario, Canada) engineers developed an artificial intelligence (AI) tool to help cancer specialists determine whether patients with breast cancer should receive chemotherapy before surgery.

Dr. Alexander Wong, a professor of systems design engineering at the university, offered his take:

“An AI system that can help predict if a patient is likely to respond well to a given treatment gives doctors the tool needed to prescribe the best-personalized treatment for a patient to improve recovery and survival.”

The Canadian researchers trained the AI algorithm using images of breast cancer made with a new MRI method they developed called synthetic correlated diffusion imaging (CDI).

Armed with knowledge obtained from CDI images of historical breast cancer cases (and information on their outcomes), the AI tool has learned to accurately predict if patients would benefit from pre-surgical chemotherapy based on their CDI images.

The team needs to validate their findings by comprehensively testing the algorithm in a larger group of patients.

AI’s Role in Drug Discovery

Finally, developing new cancer drugs is a lengthy and expensive process.

However, AI is poised to accelerate drug discovery and development by predicting which compounds are most likely effective against specific cancer types.

Machine learning models can analyze vast datasets of molecular information, including genetic mutations and protein interactions, to identify potential drug candidates.

AI can also predict how cancer cells may develop resistance to certain treatments, helping researchers devise strategies to overcome this resistance.

This knowledge is invaluable in the ongoing battle against cancer, where the disease often evolves and adapts in response to treatment.

Enhancing Patient Care and Experience

Beyond diagnosis and treatment, AI is transforming the overall patient experience and care delivery.

AI-powered chatbots and virtual assistants can give patients 24/7 access to healthcare information, answer questions, and schedule appointments.

This process enhances convenience and reduces the burden on healthcare staff, allowing them to focus on more critical tasks.

Additionally, AI can improve the quality of life for cancer patients through symptom management and supportive care.

AI algorithms can monitor patient-reported symptoms and side effects, providing timely interventions and recommendations for symptom relief. This personalized approach helps patients cope with cancer treatment’s physical and emotional challenges.

Do Chatbots Give Reliable Cancer Information?

Two recent studies conclude that:

Artificial intelligence (AI) chatbots can give accurate information to common questions about cancer but not so much when providing evidence-based cancer treatment recommendations.

One study, which looked at common cancer-related Google searches, found that AI chatbots generally provide accurate information to consumers, but the information’s usefulness may be limited by its complexity.

The researchers discovered four chatbots generated “high-quality” responses about five cancers. The chatbots did not appear to spread misinformation.

Three of the four chatbots cited reputable sources.

However, the team also found that the information usefulness was “limited” because chatbots wrote responses at a college reading level. Moreover, AI chatbots generated concise answers with no visual aids.

A separate research study assessed cancer treatment recommendations. The AI AI chatbots missed the mark on giving treatment recommendations for breast, prostate, and lung cancers in line with national guidelines.

Ethical Considerations and Challenges

While the potential of AI in cancer detection and treatment is immense, it also raises several ethical and practical challenges.

One of the primary concerns is data privacy and security. AI systems require access to vast patient data, including medical records and genetic information. Ensuring the confidentiality and protection of this sensitive data is paramount.

Another challenge is the need for regulatory oversight and standardization. AI algorithms used in healthcare must meet rigorous quality and safety standards.

There is also the issue of equity in access to AI-powered cancer care. Not all healthcare facilities and regions have equal access to AI technologies, which can exacerbate healthcare disparities.

We must ensure that AI benefits reach underserved populations and that access is not limited to affluent communities.

My Final Thoughts — Cracking the Code: How AI is Unveiling Cancer’s Secrets

Artificial Intelligence is ushering in a new era in the fight against cancer. It transforms how we detect, diagnose, and treat this complex disease.

AI’s ability to process vast amounts of data, identify patterns, and personalize treatment plans is revolutionizing cancer care, offering new hope to patients and healthcare providers.

As AI advances, we must navigate ethical and regulatory challenges, ensuring that AI-powered cancer care is accessible, safe, and equitable for all.

With ongoing research and collaboration, AI promises to unlock more of cancer’s secrets, bringing us closer to a future where cancer is not only detected early but also effectively treated and, ideally, prevented altogether.

In this battle against cancer, AI can be a powerful ally, helping us crack the code and unveil the secrets that have long eluded us.

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