Richard Young, M.S.’s Post

A study came out a few days ago that looked at the diagnostic accuracy of AI in DP A rapidly evolving area that seeks to enhance diagnostics using whole slide images The results showed that AI solutions applied to whole slide images had a high diagnostic accuracy overall (sensitivity of 96.3%, specificity of 93.3%) 𝗦𝗼, 𝘄𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗺𝗲𝗮𝗻? The high sensitivity and specificity suggest that AI has the potential to: •• Improve diagnostic accuracy and consistency compared to human pathologists •• Streamline the pathology workflow by automating certain diagnostic tasks •• To reduce variability and subjectivity in pathological assessments •• Provide decision support for pathologists (especially in complex cases) Despite the potential, more research is needed to validate AI’s utilization in DP before it can be integrated into clinical practice 𝗞𝗲𝘆 𝗮𝗿𝗲𝗮𝘀 𝗳𝗼𝗿 𝗮𝗱𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: 1) Broader evaluation across a range of diseases and sub-specialties to ensure reliability 2) Whether the AI model can consistently perform across different patient demographics and healthcare environments 3) Assessing how AI can be integrated into existing workflows and its impact on clinical decision-making 💡 As we advance, the focus must be on rigorous validation, ethical considerations, and foster a synergy between human expertise and AI. #AI #healthcare #diagnostics #digitalpathology [Link to Full Study: https://lnkd.in/eXjBQEkV]

Revolutionizing Healthcare using Generative AI This panel discussion will explore the ground-breaking potential of generative AI in revolutionizing medical care. Generative AI holds immense promise for transforming healthcare, but ethical considerations, thorough validation, and responsible implementation are essential. Careful attention to these challenges will unlock the full potential of AI to improve diagnosis, treatment, and overall patient care. However, navigating the ethical and practical challenges will be crucial to ensure equitable, responsible, and impactful implementation for the benefit of all. This expansion includes specific examples, highlights potential benefits beyond patient care, personalized diagnosis, prevention of infectious diseases and Medical image processing. The emphasis should be collaboration and stakeholder involvement in addressing the challenges. The panellists, Lakshmanan Sethu, Google, Chinmay Nerurkar, Microsoft, Ruchi Agarwal, Netflix, and Vishnu Pendyala, San Jose State University will delve into a range of crucial questions on leveraging the predictive power of GenAI for personalized medicine, enhanced diagnostics, ethical dilemmas, mental health support, privacy-preserving practices, trust and transparency, and more.

According to this article from Fast Company, Using AI for Public Impact: Insights from Dr. Soroush Saghafian AI is reshaping industries, and its integration into healthcare, public policy, and business is crucial. Dr. Soroush Saghafian, founder and director of the Public Impact Analytics Science Lab (PIAS-Lab) at Harvard, provides key insights into AI's transformative potential. Mitigating Algorithm Aversion in Healthcare: AI often outperforms medical professionals in simulations, but "algorithm aversion" limits its real-world impact. Dr. Saghafian’s work focuses on making AI systems intuitive to align with human decision-making, thus increasing their acceptance in clinical settings. Bridging AI and Public Policy: Dr. Saghafian's lab develops AI algorithms to optimize resource allocation in healthcare, crucial during crises like COVID-19. This approach not only saves money but also enhances system stability and responsiveness, paving the way for innovative healthcare solutions. Promoting Equity Through Ethical AI: Ethical deployment of AI in healthcare is essential. Dr. Saghafian advocates for balancing model accuracy with patient outcomes, emphasizing cautious inclusion of race in AI models to enhance decision-making quality without compromising trust and compliance. Overcoming Regulatory Challenges: Integrating AI in healthcare faces regulatory hurdles. Dr. Saghafian calls for updated FDA guidelines to balance safety and innovation, highlighting the need for healthcare companies to invest in compliance and proactive regulatory engagement. The Future of Predictive and Proactive Healthcare: Dr. Saghafian envisions AI-driven healthcare models that anticipate and prevent health crises. This proactive approach could transform smartphones into primary healthcare advisors, significantly enhancing preventive care. Dr. Saghafian's work underscores the technical, ethical, and regulatory frameworks necessary for effective AI integration, offering a roadmap for leveraging AI to improve public and healthcare outcomes. #aiinhealthcare With the Specialist combines artificial intelligence with a board certified neurologist to enhance neurological care in the primary care setting, bringing the neurology consult to up. #withthespecialist #neurology #innovation https://lnkd.in/e-UNEiXw https://lnkd.in/gExrwg2P

"🚀 Excited to share my latest blog post on how AI is transforming healthcare! From improving medical imaging to predicting epidemics, AI is not just assisting but radically changing patient care and health operations." Key highlight: AI in medicine is projected to grow at an annual rate of 48%. Read more to discover how AI is dosing the healthcare sector with innovation: https://lnkd.in/gE3a_equ #HealthcareAI #ArtificialIntelligence #HealthTech #MedicalInnovation #FutureOfHealthcare" Koshys Group of InstitutionsKoshy's Business School

How Generative AI Can Help Clinicians Interpret ABG Test Results - HealthTech Magazine Title: How Generative AI Can Help Clinicians Interpret ABG Test Results #Introduction Generative AI technology is revolutionizing the healthcare industry by assisting clinicians in interpreting arterial blood gas (ABG) test results more effectively. #Understanding ABG Tests ABG tests provide vital information about a patient's respiratory and metabolic status, including pH levels, oxygen and carbon dioxide levels, and bicarbonate levels. #Challenges in Interpreting ABG Tests Clinicians often face challenges in accurately interpreting ABG test results due to the complexity of the data and the need for quick decision-making. #Benefits of Generative AI Generative AI algorithms can analyze ABG test results quickly and accurately, providing clinicians with valuable insights to make informed treatment ai.mediformatica.com #healthtech #healthcare #clinicians #medical #generativeai #washington #amazon #patients #medication #amazonwebservices #careteam #medicalerrors #digitalhealth #healthit #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/3WgSdkS)

Mount Sinai Health System plans to integrate #AI into all its #ITsystems within five years. Dr. Bruce Darrow highlights AI's transformative impact on #patientcare, from predicting illnesses to streamlining operations. Key Insights - ▶ Impact: Early detection of critical conditions, improved diagnostic accuracy, and operational efficiency. ▶ Principles: Guided by safety, effectiveness, equity, and ethics. ▶ Future: AI will soon be embedded in all healthcare systems. Questions to Ponder - ▶ How will AI change the roles of healthcare professionals? ▶ What are the ethical considerations of AI in healthcare? ▶ Mount Sinai's AI journey is a testament to the future of healthcare. #HealthcareInnovation #MountSinai #FutureofMedicine

AI is reshaping the landscape of healthcare, bringing precision and innovation to patient care. Here's how AI is revolutionizing the field: 🌐 AI and machine learning are significantly enhancing diagnostics, treatments, and patient outcomes, establishing a foundation for what is projected to be a $188 billion industry by 2030. 🩺 From diagnostic radiology to neurology, AI is helping healthcare professionals make faster, more accurate decisions that directly improve patient care. 📊 Beyond direct patient interaction, AI improves the efficiency of research and administrative operations, enhancing the overall healthcare delivery system. 🤖 Leading institutions like Cleveland Clinic are spearheading global collaborations to promote the ethical use of AI in healthcare, ensuring its development and application are responsible and safe. 🔬 The integration of AI is continuously expanding our understanding of complex medical conditions and paving the way for innovative treatment approaches. #HealthcareAI #Innovation #DigitalHealth #AIMedical #TechInMedicine #AIResearch #EthicsInAI #AIFuture #FutureOfHealthcare #AIDiscovery #HealthTech #MachineLearning https://lnkd.in/gcigD5xr

The evolution of healthcare AI models, from LLMs to LMMs, is profoundly advancing care, patient engagement, and outcomes, particularly in hyperpersonalization and cancer care. These sophisticated AI systems analyze vast datasets to deliver highly personalized treatment plans, enhancing the precision of cancer therapies and patient interactions. As we harness the transformative power of LMMs, a crucial focal area for future exploration is the integration of responsible AI principles—fairness, privacy, equity, transparency, and accountability—throughout the model development process. This ensures that advancements in AI not only drive innovation but also uphold the highest standards of ethical integrity and patient trust. It was great to read the open-access paper released by Google and DeepMind highlighting their newest artificial intelligence tools intended for use in healthcare. An insightful article by Emma Beavins. #AIinHealthcare #LMM #PersonalizedCare #ResponsibleAI #PatientEngagement

Summary and Opinion Artificial Intelligence (AI) is revolutionizing the fields of science and healthcare, offering unprecedented opportunities for advancements in research, diagnostics, and patient care. Three recent articles highlight the profound impact of AI on these sectors, showcasing diverse perspectives and recent developments.

What’s happened this week in the healthcare & AI world? Here is the interesting news and research: 𝐍𝐞𝐰𝐬: 🗞 An AI triage service has reduced patient wait times by 73% for a GP practice. 🗞 The Gov will launch a Regulatory Innovation Office to help regulators remove barriers to tech in places like the NHS. 🗞 The 2024 State of AI Report was published yesterday by Air Street Capital, and notes the commercial “vibe-shift” from existential threat to sales & usage - Oliver Patel, AIGP, CIPP/E published a good report summary. 🗞 Imperial will trial AI to support cancer diagnosis in general practices. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡: 👩💻 Using deepfakes in psychotherapy, eg for a guided encounter with a deceased loved one, could (unsurprisingly) need new protections (Eg to stop an over-attachment that could stagnate the acceptance of loss).* *this paper is a older than this week but is circulating right now. 👩💻An analysis finds that AI for global health is a hyped topic, but in practice the determinants of health are being side stepped. 👩💻 Interviews with German med students on AI-CDSS found future clinicians have two different attitudes: “the one relying [on]” vs “the one controlling” the AI. P.S. What item was most interesting to you this week?