Stephen Pittman

There is a new (substantial) market coming for video games and other forms of media that can positively impact mental health. The Digital Therapeutics Alliance has been working hard with congress to create new reimbursement pathways for media as medicine (Digital Therapeutics) - with a special focus on mental health. Reference Article: https://lnkd.in/gxWwQTks Many commercial video games have been proven to positively impact mental health. One of over 200 Reference Studies: https://lnkd.in/gSYzZKsi The Immersive Medicine Network - a collaborative ecosystem of game developers, experience designers and medical professionals has been created to help media professionals access this new market: The Immersive Medicine Network is building the following resources: - A resource website for creating media as medicine: www.immersivemedicine.org - A LinkedIn support group, the Immersive Medicine Network (IMN) where connections can be made and resources shared: https://lnkd.in/gW8M_vXN - A Podcast to help spread information (first episode coming this week) - A biweekly fireside chat, where questions can be asked and collaborative approaches developed. (Accessible through the IMN) Media holds the key to delivering vital mental and physical health interventions at scale. Now the industries must learn to combine capabilities to create the change we need to fight the #loneliness #stress #anxiety and #depression that are crippling our society. Please join us as we build this new world of Immersive Medicine, recognizing the therapeutic potential of media and bringing accessibility and affordability to mental health care. #videogames #immersivemedicine #powerofplay #stressrelief #resilience

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“Cardiology continues to have the second largest number of clinical artificial intelligence (AI) algorithms cleared by the U.S. Food and Drug Administration, trailing only radiology. The FDA's latest update covers all AI approvals through May 2024. There are now 122 FDA-cleared AI algorithms specific to cardiology. This makes up 14% of the 882 clinical AI algorithms now on the U.S. market. The new FDA numbers include market clearances up to March 31, 2024. The first approval of a clinical AI algorithm was in 1995. The first cardiology specific algorithm was for HeartFlow FFR-CT in 2016. That algorithm was also the first AI to be included in a cardiology guideline when the 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain was released.” MedTech Innovator American Heart Association #epeeps Heart Rhythm Society American College of Cardiology LSI Capital Factory Company Ventures MedTech Strategist Health Wildcatters Techstars

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🌟 Generative AI and Healthcare Transformation: A New Era of Innovation 🌟 I am constantly asked about #AI applications for healthcare transformation. I continue to take people back to the pain points or problems being solved. The healthcare industry is undergoing a significant transformation, driven by the integration of generative AI. This revolutionary technology is currently reshaping the way we approach care management, early disease detection, and administrative tasks. Early Benefits of Generative AI: Enhanced Care Management: AI serves as a "co-pilot" for healthcare professionals, assisting in managing patient care more efficiently and accurately. This leads to improved patient outcomes and more personalized care plans. Early Disease Detection: AI's ability to analyze vast amounts of unstructured data enables early identification of diseases, potentially saving lives and reducing healthcare costs. It's a game-changer in preventive healthcare. Reducing Clinician Burnout: By automating repetitive administrative tasks, AI allows clinicians to focus more on patient care. This not only improves job satisfaction but also enhances the quality of care provided. Affordability and Efficiency: AI-driven processes streamline operations, making healthcare more affordable and accessible. From optimizing workflows to reducing operational costs, AI is paving the way for a more sustainable healthcare system. Challenges and Considerations: Ethical and Legal Frameworks: Ensuring AI is used responsibly requires robust ethical, legal, and policy frameworks. Trustworthy AI adoption is crucial for patient safety and health equity. Technology Infrastructure: Organizations need to update their technology infrastructure, including cloud capabilities, to fully support AI implementation. As we embrace these advancements, it's essential to stay informed and engaged in the conversation about how AI can continue to transform healthcare for the better. #HealthcareTransformation #GenerativeAI #HealthTech #Innovation #AIinHealthcare Thanks to sources McKinsey & Company (https://lnkd.in/g7HZHEST) and MedCity News (https://lnkd.in/gi95t4qJ)

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After a brief writing hiatus… Part III of “Who Pays for Healthcare AI” is live. The third installment defines five performance-based pricing models for healthcare AI and explores: • Four types of Return on Investment (ROI) in healthcare and life sciences • The importance of shielding at-risk pricing models from operational externalities • How better pricing model design can mitigate negative working capital risk under performance-based models • Taming the beast: attribution Check out Part III below, and subscribe to receive the final post of the series! https://lnkd.in/dPZSHMiy

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Interesting cardiology subplot to Signify Research Ltd's latest imaging AI startup funding data. The 15 most-funded imaging AI companies include five cardiovascular-focused startups (HeartFlow, Inc, Cleerly, CathWorks, Keya Medical, Elucid), and three companies that place a heavy focus on cardiovascular and stroke imaging (Aidoc, Viz.ai, RapidAI). ...That's more than half of the imaging AI companies that have raised over $100M. Considering that the majority of AI vendors focus on non-cardiovascular imaging, this says a lot about where VCs have been spending their money -- closer to care, procedures, costs, and reimbursements. We'll be covering this in the next Cardiac Wire https://lnkd.in/gffPtj9J

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NEJM AI Volume 1, No. 5 is now live! This issue covers a number of urgent concerns for AI x biomedicine, including: • LLM underperformance on automated medical coding tasks • Challenges of integrating AI into traditional healthcare reimbursement models • The effectiveness of histology image search algorithms • Ethical questions for patients engaging with AI tools in their healthcare • Comparative evaluation of AI systems in diagnosing Mendelian disorders Visit http://ai.nejm.org to read all the latest articles on AI in medicine! #healthcare #ai #artificialintelligence #generativeai

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#BiomedTech #Startups #Funding Biotech Funding Surge: Top Startups Raise $2.9B in Q1 2024” -Record Funding: The top 20 healthcare-focused biotech companies collectively raised $2.9 billion in Q1 2024, marking a 161% increase compared to the previous year. -Market Confidence: Investors are making more confident bets on the market viability of promising healthcare biotechnology firms. -Focus Areas: Funding recipients include companies specializing in precision oncology, AI-driven drug discovery, cell and gene therapies, and novel approaches to treating autoimmune disorders. Alumis Alumis (formerly Esker Therapeutics) secured $529M in cumulative funding, focusing on precision immunology and targeted treatments for autoimmune diseases. Freenome Freenome, a leader in early cancer detection, raised $1.35B in total funding for its multiomics screening platform. #BiotechFunding #HealthcareInnovation #PrecisionMedicine #HealthTech #LifeSciences #InvestmentNews #HealthcareStartups #InnovationFunding Ahmed-digital doc- Otokiti MD, MBA, MPH Alister Martin Philippe GERWILL Umer Khan M. Karim Beguir Harvey Castro, MD, MBA. Gabriella Marcelja

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“Eko Health, the California-based healthcare technology company known for its advanced stethoscopes, has received U.S. Food and Drug Administration (FDA) approval for a new artificial intelligence (AI) offering designed to detect low ejection fraction (EF). The newly approved algorithm is designed to work in just 15 seconds; it automatically runs when users conduct routine physicals with one of Eko Health’s stethoscopes. Eko Health developed this AI offering with heart failure in mind. By getting the technology in the hands of physicians, the company hopes symptomatic patients can be identified earlier than normal, improving their chances of receiving the care they need. Low Ejection Fraction AI is the latest addition to Eko Health’s Sensora Cardiac Early Detection Platform. It joins other FDA-approved algorithms for identifying signs of atrial fibrillation and structural heart murmurs.” American Heart Association MedTech Innovator MedTech Strategist Heart Rhythm Society #epeeps American College of Cardiology

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🤔FDA approved the first AI/ML device in 1995! 👉But the pace started increasing only after 2016. ❗Device approvals grew at a CAGR of 49% between 2016 and 2023. WOW! 💥 😲Now, there are 882 AI/ML devices on the updated FDA list as of March 2024. 👇Learn more about AI/ML device trends in the article below (see link in comments). ======================================= 💗 this post? ♻️Repost with your own insight. #riskmanagement #letstalkrisk #medicaldevices

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Tempus AI sold 11.1 million shares at the #top 🚀 of the range for $37 each; after offering them for $35 to $37. At the IPO price, the company has a market value of $6.1 billion. Founded in 2015, Tempus is creating an intelligent diagnostics platform for precision medicine ⚕. Positive news for #AI ; #digitalization and #data companies in healthcare that this IPO went through - at top of range pricing. The journey ahead won't be linear, but looking forward what's come. https://lnkd.in/eudTHqkC

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IBM isn’t the first to explore machine learning’s place in healthcare. Medical device firm Philips has sought to patent AI-based systems that predict emergency room delays and reconstruct medical imagery. Google filed a patent application for a way to break down and analyze doctors’ notes using machine learning. On the consumer end, Apple has researched ways to put the Vision Pro to use in clinical settings using a “health sensing” band. AI has a lot of promise in the healthcare industry in areas such as documentation, imaging, and quicker diagnostics as staffing shortages loom. The problem, however, is the data. For one, in the US, healthcare data is strictly protected under the Health Insurance Portability and Accountability Act (HIPAA). And given that AI needs a lot of high-quality data to operate properly, it’s particularly difficult to build models for healthcare settings. Though synthetic data may present a solution, because these models are being used in an area where accuracy is important, authentic data would likely allow for a more robust model — especially since lacking data leads to the dreaded issue of hallucination. The other problem lies in how data is treated beyond training. Because AI has known data security problems, it may be difficult to get patients to trust models with their most sensitive information. https://lnkd.in/g8kQwZbP

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Using 'representation vectors' instead of prompt engineering to modulate #LLM responses enables tuneable behavior: https://lnkd.in/eUwSUvtg

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Very impressed to see what the team at Department of Biomedical Engineering, Boston University and Hadi T. Nia is doing with the STEP (ISO 10303) standards while study the issues related to lung cancer. We should support this team with long term data retention of such information of their FEM data and map the C3D10 quadratic tetrahedral elements to the AP209 data model, allowing them to do correlations for any test samples in the future. https://lnkd.in/d_H-aE4n

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Telemedicine and digital therapeutics are shaping the future of medtech. The convenience and accessibility of telemedicine have made it a staple in healthcare, especially for patients with budget or geographic constraints. Digital therapeutics, often AI-based, are enabling clinicians to manage and treat diseases remotely, improving efficiency and patient outcomes. The rise of these technologies underscores the importance of staying updated with medtech trends. As the industry continues to evolve, it's crucial to keep abreast of the latest innovations and opportunities. Stay informed and ahead of the curve with the latest insights and trends in medtech by subscribing to our LATAM Medtech Pulse here: https://lnkd.in/efHSwknX. #Telemedicine #DigitalTherapeutics

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#Niche-focused #ventures in #HealthTech, such as those #targeting #underserved areas or #specific health conditions, offer several benefits. They can address gaps in the #healthcare system, provide specialized care, and #potentially integrate into broader #ecosystems for comprehensive healthcare solutions. For example, #JVEDTECHMedovation, could explore #partnerships with #niche #HealthTech startups to enhance offerings in healthcare #innovation.

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There appears to be a "Superstar Effect" in healthcare and biomedical AI research right now. A small percentage of publications are truly novel methods contributions that introduce new capabilities or behaviors; whereas a majority of contemporary research publications are focused on implementation science to assess the real-world utility and performance of new methods. This dynamic seems different from prior eras, when the translational infrastructure for implementing novel AI methods was largely unavailable. While methods research often captures more attention and accolades, both types of research are critical – novel methods without implementation science lacks translatability; implementation science without novel methods lacks novelty. If our goal is to invent and deploy transformative AI methods in real-world healthcare and life sciences contexts, we ought to continue encouraging and rewarding stellar implementation science work alongside breakthrough methods development.

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💥 Magnificent cell division video. Have you ever seen this? Cell division involves a single cell splitting into two identical daughter cells through mitosis, which includes prophase, metaphase, anaphase, and telophase, followed by cytokinesis. This process is essential for growth, repair, and tissue maintenance in multicellular organisms. 🧬 Understanding cell division is crucial for cancer treatment because cancer arises from uncontrolled cell division. Targeting specific stages of this process allows for the development of therapies that can inhibit cancer cell proliferation, reduce tumor growth, and potentially lead to more effective treatments with fewer side effects by selectively targeting cancerous cells. Video from zaparray #cancertherapy #cancervaccines.

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