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Important share from our sister publication, Inside Precision Medicine below. As AI hits the diagnostics mainstream, I’m sincerely hopeful that advanced-stage cancers in patients willing to be screened will soon become a historical footnote. Recent research published in JAMA Network Open reveals that AI isn’t just helping radiologists detect breast cancer at the time of screening—it’s also identifying women at risk years before a diagnosis might occur. In this study, commercially available AI algorithms analyzed mammograms and provided scores indicating a suspicion of breast cancer, even when the cancer wasn’t yet visible to the human eye. These algorithms not only mark areas of immediate concern but also highlight imaging features associated with cancers that may develop years later. This breakthrough could lead to more personalized, earlier screening and prevention strategies, which may allow us to diagnose breast cancer in its earliest stages and avoid more aggressive treatments. Thanks for sharing this, Damian Doherty! The authors note: “Although current commercial AI tools, such as the one used in our study, were not developed or optimized for future cancer risk estimations, we found that the AI system’s discriminatory accuracy for estimating future screening-detected or interval cancer risk 4 to 6 years before diagnosis met or exceeded the performance of established risk calculators currently in wide use.” With regulatory approvals in place and promising results like these, AI is rapidly becoming a key player in radiology and oncology. The potential to detect cancer earlier and tailor screenings more effectively could reshape how we approach cancer care, leading to better outcomes and longer, healthier lives. The future of cancer care is bright, and AI is helping us take a significant step forward in preventing advanced-stage disease before it can even begin. #AIinHealthcare #BreastCancerAwareness #EarlyDetection #PrecisionMedicine #FutureOfOncology Inside Precision Medicine AI in Precision Oncology Marianne Russell Bill Levine Damian Doherty

I'm excited to share a sneak peek of my recent interview with Dr. Cliff Hudis, CEO of ASCO, in this month’s upcoming issue of AI in Precision Oncology. Cliff has been a personal oncology hero of mine since my early days as a breast cancer doctor, so it was a real honor to sit down with him. During our conversation, Dr. Hudis offered some great insights on the responsible integration of AI in cancer care. Here's one standout quote: "...we can start to gain meaningful efficiencies and improve the quality of our work and lives with these tools, as has happened outside of healthcare. Our slowness in this regard is frustrating but sadly consistent: It’s jaw-dropping insanity that the single biggest users of fax machines on Earth anymore are in American healthcare. It’s inefficient. It is insecure. So optimistically, I think we’re going to turn the corner, and things are going to get better. Our job, and what you’re trying to do here, is to educate people about what’s happening now and help us move this process along." Here is a link if you'd like to check out this piece and more at AI in Precision Oncology: AI in Precision Oncology : (liebertpub.com) American Society of Clinical Oncology (ASCO) Conquer Cancer, the ASCO Foundation Clifford Hudis Robin Zon Julie Gralow Debra Patt, MD PhD MBA Nikhil Thaker, MD Mary Ann Liebert, Inc.

We are thrilled to announce that Olalekan Ajayi PharmD MBA FACCC, is joining the AI in Precision Oncology Editorial Board. As Chief Operating Officer of Highlands Oncology Group, a large multi-specialty oncology practice, Lekan brings deep expertise in practice Artificial Intelligence applications, particularly in Business Intelligence—from staffing optimization to capacity management and other operational applications. His practical leadership in these areas will help guide decision-makers looking to implement AI within their systems. Lekan's influence in the oncology field is vast. As a past president of the Association of Cancer Care Centers (ACCC), overseeing over 42,000 members, he has influenced cancer care nationwide. In 2023, he was recognized as the Leukemia and Lymphoma Society's Visionary of the Year, highlighting his innovative approach and contributions. Lekan will play a key role in reviewing manuscripts focused on operational efficiencies, ensuring necessary research reaches decision-makers facing questions about AI integration in the business of cancer care. Welcome, Lekan! We’re excited to have you on board! #AIinOncology #BusinessIntelligence #Leadership #PrecisionMedicine #HealthcareInnovation

⏳ Just 2 weeks to go until the Clinical Pathways Congress + Cancer Care Business Exchange in Boston! The event brings together industry leaders, healthcare professionals, researchers, payment reform experts, and innovators to discuss and showcase transformative oncology delivery, payment, and business models. I am excited to participate in this panel with James Hamrick, Jeff Hunnicutt, and Will Shapiro. These are important topics, and these guys know their stuff. By exploring innovative strategies and solutions, we aim to transform the current cancer care landscape, ensuring better access, higher quality care, and improved patient outcomes. Together, we will delve into complex topics such as the role of AI in oncology, the significance of and barriers to effective clinical trial recruitment in the community setting, the power and impact of vertical integration, trends in practice consolidation, the EOM outlook from diverging perspectives, and so much more. We invite you to refine your approach in Boston on September 6–8, 2024. 🔑 Use code VIP to save 15% on registration. https://lnkd.in/gmCpcGgW #pathwaysexchange #clinicalpathwayscongress #cancercarebusinessexchange #TensorBlack AI in Precision Oncology TensorBlack

Sharing an informative article for leaders that includes updated research from McKinsey about embracing the next inflection point in AI: As Generative AI (Gen AI) progresses from employee experimentation to organizational transformation, its potential to reshape industries is immense. According to McKinsey, HALF of today’s work activities could be automated between 2030 and 2060, accelerating previous projections by a decade. This acceleration places immense pressure on organizations to rapidly identify talent needs, close skill gaps, and invest in upskilling and reskilling. Key insights: - Nearly two-thirds of early adopters of Gen AI have a clear strategy to close talent gaps, compared to just 25% of experimenters. Upskilling and reskilling are crucial; hiring alone isn't enough, and outsourcing can hinder strategic skill development. - 40% of early adopters provide extensive support for employee adoption, compared to only 9% of experimenters. - Investing in talent and infrastructure is crucial for harnessing Gen AI's potential. Successful implementation requires strong leadership and a clear vision to drive efficiency, innovation, and growth. Prepare to revolutionize your organization with Gen AI. Share the comprehensive article below with your organization's leaders to explore how your team can invest and remain at the forefront of the AI revolution. #AIRevolution #TechInnovation #FutureOfWork #DigitalTransformation #LeadershipInAI AI in Precision Oncology TensorBlack Total Health | Oncology

AI: Transforming Primary Care Amid Critical Shortages This week, I came across a deep discussion between Peter Attia and Isaac Kohane on Peter's podcast, The Drive. They tackled the transformative potential of AI in healthcare, especially amid critical primary care shortages. "AI isn't about replacing doctors but supporting care where it's needed most," Kohane emphasizes. This conversation comes at a crucial time when patients increasingly use AI-driven tools for initial diagnoses and healthcare advice, driving grassroots disruption in the medical field. For the TLDR crowd, see the comments below for a nice summary of the topics covered from yesterday's Timmerman Report. On the podcast, Zac shares his journey with AI, from its early iterations to the current third generation, and highlights significant advancements, "The potential for AI to democratize healthcare by making advanced diagnostics accessible to underserved areas is immense," says Kohane. I'm very excited that patients in rural or disadvantaged communities might have better access to local care. This capability could alleviate some of the current strain on primary care by providing reliable, immediate healthcare support to patients who might otherwise have limited access to medical professionals. They also spent some time addressing the remaining substantial challenges. Integrating AI into clinical practice involves navigating data privacy concerns and regulatory barriers and ensuring seamless interoperability with existing healthcare systems. Kohane points out, "The future of AI in healthcare relies on collaboration between technologists, clinicians, and patients." This collaboration is essential to developing and implementing AI tools effectively and ethically. AI offers the potential to enhance diagnostics, improve patient outcomes, and address critical shortages in primary care. However, it is crucial to implement these technologies thoughtfully, ensuring they complement and support human expertise rather than replace it. Staying informed and engaged with these developments is essential as we move forward. Integrating AI in healthcare is not just a top-down initiative but a collaborative effort requiring all stakeholders' input and cooperation. Embracing AI's potential could lead to a more efficient, accessible, and effective healthcare system for everyone. #HealthcareInnovation #AIinMedicine #PrimaryCare #PatientCare #HealthcareDisruption

One more to read over this morning’s coffee. I’m truly grateful for the American Society of Clinical Oncology (ASCO) and its leadership for their hard work in navigating the future of AI in oncology. As a 20-year member of ASCO, I love seeing our professional society taking proactive steps to address the complexities and opportunities that AI presents in cancer care. Kudos, Clifford Hudis, Julie Gralow, Christopher Merlan, Debra Patt, MD PhD MBA, Jeremy Warner, Caroline Chung for your strong leadership in these crazy times! Recently, ASCO released the “Principles for the Responsible Use of Artificial Intelligence in Oncology.” These principles are designed to help the oncology community safely and effectively leverage AI for the benefit of patients and clinicians worldwide. Here are the six guiding principles that will shape ASCO’s approach: 1. Transparency: AI tools and applications must be transparent throughout their lifecycle. 2. Informed Stakeholders: Both patients and clinicians should be aware when AI is utilized in clinical decision-making and patient care. 3. Equity and Fairness: It’s crucial to protect against bias in AI model design and use, ensuring equitable access to AI tools. 4. Accountability: AI systems must comply with legal, regulatory, and ethical standards, with developers taking responsibility for their AI systems and their decisions. 5. Oversight and Privacy: Institutional compliance policies must govern AI use, protecting clinician and patient autonomy and personal health information privacy. 6. Human-Centered Application: AI should complement, not replace, human interaction in healthcare, preserving the essential human touch in patient care. As we step into this new era of AI-supported cancer care and research, I’m genuinely excited about the potential benefits for our patients and the healthcare system as a whole. ASCO’s commitment to thoughtful deployment and monitoring of AI ensures that we can make the most of this technology ethically and effectively. I’d love to hear your thoughts on AI in oncology. How do you see it changing our field? Let’s get a conversation going! 👇 #AI #Oncology #CancerCare #HealthcareInnovation #ASCO #MedicalEthics #FutureOfMedicine AI in Precision Oncology Mary Ann Liebert, Inc. TensorBlack