Transforming Healthcare with Responsible AI: A UniqueMinds.ai Perspective The rapid integration of AI into healthcare is a game changer, with nearly 1,000 FDA-authorized AI-enabled medical devices now shaping patient outcomes. This milestone demonstrates the power of innovation and the responsibility we bear as leaders in this space to ensure AI is developed and deployed ethically and effectively. At UniqueMinds.ai, we believe this is where our Responsible AI Framework for Healthcare (RAIFH) truly shines. The RAIFH principles—spanning Fit for Use, Accuracy, Transparency, Privacy, Security, Fairness, and Accountability—align seamlessly with the FDA's total product life cycle approach for AI regulation. By embedding these principles into every phase of an AI solution’s journey, from design to post-market monitoring, we not only ensure compliance but also champion trust, equity, and value creation in healthcare innovation. As FDA Commissioner Dr. Robert M. Califf highlights, a comprehensive strategy that integrates real-world data and global collaboration is key to maintaining the balance between technological advancement and patient safety. RAIFH enhances this vision by offering actionable guidance that empowers healthcare stakeholders to navigate the complexities of responsible AI adoption. The healthcare landscape is evolving rapidly, and we’re proud to lead the way in ensuring that innovation remains grounded in values that prioritize patient safety, equity, and trust. I invite healthcare leaders and innovators to join the conversation on driving responsible AI adoption—let’s work together to ensure every AI solution is not just innovative but responsible as well. #InsideUniqueMinds #AIinHealthcare #ResponsibleAI #RAIFH https://lnkd.in/gmiVNk93
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As artificial intelligence (AI) advances across healthcare, it’s crucial for regulatory frameworks to keep pace. The FDA has authorized nearly 1,000 AI-enabled medical devices, marking significant progress, but new approaches are needed to evaluate AI's unique challenges in clinical care and medical research. Strong FDA oversight will play a pivotal role in fostering safe, effective, and trustworthy AI in healthcare. Read the full article here: https://lnkd.in/eXtikgzb
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Access and reimbursement pathways for digital health solutions and in vitro diagnostic devices: Here is how I can help your organization. The main goal of healthcare, pharma, and medtech companies is to treat patients better. So if we take a step back, we can see that any area that AI & ML models would impact, connects to patient care, from prevention and diagnosis to drug development and bedside care. Evaluating the efficacy of digital health initiatives is crucial for healthcare executives. I specialize in leading organizations through their digital transformation journey, offering expertise in various areas: - Application of predictive analytics, artificial intelligence, and machine learning in early and accurate disease detection, chronic illnesses, medical care delivery and enhancing the patient experience in healthcare. - Assessment of the US, EU 5 & China policy environments. - Explaining digital health reimbursement pathways. - Understanding payer archetypes and their evidence requirements. - Generating health economic evidence. - Developing local market business models. - Providing affiliate training. - Conducting payer negotiations and contracting. Let's discuss how I can add value to your initiative. #digitalhealth #oncology #opportunities #medicine #clinicalresearch #research #strategy #innovation #environment #training #access #rarediseases #hematology #cardiovascular #diabetes #respiratory #immunology #patientaccess #pricing #reimbursement #director #multiplesclerosis #metabolic #mentalhealth #marketaccess #populationlevelfunding #neurology #asthma #copd #healthcare #marketing #monetization #businessmodel #healtheconomics #value #commercialization
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🤖 Key Highlights from the Systematic Narrative Review on Generative AI in Clinical Services 🔍 Generative AI (GenAI) Usage Trends in Healthcare 🔹 GenAI tools are increasingly utilized by healthcare professionals as knowledge aids, dialogue facilitators, and training resources. 🔹 Applications are focused on disease detection, diagnosis, and screening, especially in radiology, cardiology, gastrointestinal medicine, and diabetes care. 💡 Preliminary Insights 🔹 Knowledge Accessibility: 87.6% of reviewed studies emphasize GenAI's role in making crucial medical knowledge accessible and actionable. 🔹 Automation Gap: Only 11.18% of studies reviewed report on GenAI’s role in automating clinical services, highlighting the need for further development in this area. ⚠️ Challenges and Missed Opportunities 🔹 Service Value Creation: Current implementations of GenAI do not fully realize their potential to create direct value in healthcare, particularly in advancing systems and personalized medicine through knowledge reuse. 🔹 Drug Development Potential: Despite being outside the primary scope, integrating GenAI into drug development and clinical trials remains a significant untapped opportunity for value creation. 🏥 Pathways for Patient-Centered GenAI Adoption 🔹 User-Centered Design: A design approach focused on user needs can help GenAI transcend traditional models based on basket data or end-point labels, enhancing its relevance in clinical research and healthcare service delivery. 🔹 Organizational Capabilities: Establishing robust organizational frameworks is essential for effectively embedding GenAI into healthcare systems and unlocking its full potential. This review highlights the importance of validating GenAI's role in clinical service delivery and emphasizes the need for patient-centered approaches to maximize its transformative impact in healthcare. Yim D, Khuntia J, Parameswaran V, Meyers A. Preliminary Evidence of the Use of Generative AI in Health Care Clinical Services: Systematic Narrative Review. JMIR Med Inform 2024;12:e52073, doi: 10.2196/52073 🔗 https://lnkd.in/dxrEs7ey #GenerativeAI #AIInHealthcare #DigitalHealth #ClinicalInnovation #PatientCenteredCare #PersonalizedMedicine #InnovationInHealthcare #KnowledgeAccess #AIAdoption
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The buzz word across the sectors has been Artifical Intelligence (AI) throughout the year 2024 🔊 💡 Are you curious to know how AI has been adopted in manufacturing of medical devices, and drug development process 🤔 💊 ⚕ 🏢 FDA's perpective on AI sheds interesting insights and few highlights are ▪ FDA intends to take flexible approach across range of AI models used for administrative healthcare offices vs models embedded in traditional medical devices. ▪ There isn't a Large language model (LLM) authorized by FDA yet and requires proactive engagement among clinicians, developers, regulators to mitigate significant risks posed by clinical decision-making tools. ▪ Focus on health outcomes is need of an hour while we continue to adopt in using AI models to overcome the pressure on the health care systems and not merely looking at as financial return on investment. #AI #Innovation #Regulations #medicaldevices #drugdevelopment #healthcare https://lnkd.in/gzGVQQHg
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Health Canada is close to publishing new guidance on AI/machine learning (AI/ML) medical devices, which includes incorporating predetermined change control plans (PCCPs). Speaking at the 2024 Medtech Conference, Marc Lamoureux, manager of the Digital Health Division, highlighted three key challenges in the AI/ML space: algorithmic drift, transparency, and postmarket monitoring. He emphasized that AI/ML models need continuous updates to maintain performance, and transparency is critical for trust and adoption. Health Canada’s draft guidance, released in September 2023, takes a total product lifecycle approach, addressing issues like bias and the need for postmarket monitoring. Regulatory provisions will ensure higher-risk devices are closely monitored. Lamoureux also noted Health Canada is adopting PCCPs, following the lead of the US FDA and Japan’s regulatory agency. The final guidance will be published soon.
Health Canada digital health head says AI/ML guidance imminent https://lnkd.in/gkrc4Up9 Health Canada is close to publishing new guidance on AI/machine learning (AI/ML) medical devices, which includes incorporating predetermined change control plans (PCCPs). Speaking at the 2024 Medtech Conference, Marc Lamoureux, manager of the Digital Health Division, highlighted three key challenges in the AI/ML space: algorithmic drift, transparency, and postmarket monitoring. He emphasized that AI/ML models need continuous updates to maintain performance, and transparency is critical for trust and adoption. Health Canada’s draft guidance, released in September 2023, takes a total product lifecycle approach, addressing issues like bias and the need for postmarket monitoring. Regulatory provisions will ensure higher-risk devices are closely monitored. Lamoureux also noted Health Canada is adopting PCCPs, following the lead of the US FDA and Japan’s regulatory agency. The final guidance will be published soon.
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From pharmaceutical research to predictive analytics to virtual mental health therapy, artificial intelligence is helping healthcare providers and patients. Learn more about how AI is making an impact on, if not radically transforming, healthcare, as well as how Michigan Tech College of Computing's graduate programs can help you keep pace with these changes and challenges. https://lnkd.in/gM9ePUie
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See ⤵️ summary by Dimitrios Kalogeropoulos, PhD on opportunities in use of AI in clinical services including: ➕Advancing systems and personalized medicine through knowledge reuse ➕Drug Development Potential ➕Pathways for Patient-Centered GenAI Adoption OncoAlert
CEO Global Health & Digital Innovation Foundation | UCL GBSH Health Exec in Residence | EU AI Office GPAI CoP | PhD AI in Medicine | IEEE Global Policy Caucus | Chair, IEEE GenAI Climate-Health Program | Speaker
🤖 Key Highlights from the Systematic Narrative Review on Generative AI in Clinical Services 🔍 Generative AI (GenAI) Usage Trends in Healthcare 🔹 GenAI tools are increasingly utilized by healthcare professionals as knowledge aids, dialogue facilitators, and training resources. 🔹 Applications are focused on disease detection, diagnosis, and screening, especially in radiology, cardiology, gastrointestinal medicine, and diabetes care. 💡 Preliminary Insights 🔹 Knowledge Accessibility: 87.6% of reviewed studies emphasize GenAI's role in making crucial medical knowledge accessible and actionable. 🔹 Automation Gap: Only 11.18% of studies reviewed report on GenAI’s role in automating clinical services, highlighting the need for further development in this area. ⚠️ Challenges and Missed Opportunities 🔹 Service Value Creation: Current implementations of GenAI do not fully realize their potential to create direct value in healthcare, particularly in advancing systems and personalized medicine through knowledge reuse. 🔹 Drug Development Potential: Despite being outside the primary scope, integrating GenAI into drug development and clinical trials remains a significant untapped opportunity for value creation. 🏥 Pathways for Patient-Centered GenAI Adoption 🔹 User-Centered Design: A design approach focused on user needs can help GenAI transcend traditional models based on basket data or end-point labels, enhancing its relevance in clinical research and healthcare service delivery. 🔹 Organizational Capabilities: Establishing robust organizational frameworks is essential for effectively embedding GenAI into healthcare systems and unlocking its full potential. This review highlights the importance of validating GenAI's role in clinical service delivery and emphasizes the need for patient-centered approaches to maximize its transformative impact in healthcare. Yim D, Khuntia J, Parameswaran V, Meyers A. Preliminary Evidence of the Use of Generative AI in Health Care Clinical Services: Systematic Narrative Review. JMIR Med Inform 2024;12:e52073, doi: 10.2196/52073 🔗 https://lnkd.in/dxrEs7ey #GenerativeAI #AIInHealthcare #DigitalHealth #ClinicalInnovation #PatientCenteredCare #PersonalizedMedicine #InnovationInHealthcare #KnowledgeAccess #AIAdoption
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Curious about how AI and the Internet of Medical Things (IoMT) are transforming patient care? Our latest article delves into groundbreaking advancements in personalized medicine, real-time health monitoring, and cutting-edge drug discovery. Don't miss out on this exciting read! Click to learn more about the innovations shaping the future of healthcare. 👉 https://lnkd.in/d35g8GHY #HealthcareInnovation #AI #IoMT #PersonalizedMedicine #MedicsInTech
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Health Canada digital health head says AI/ML guidance imminent https://lnkd.in/gkrc4Up9 Health Canada is close to publishing new guidance on AI/machine learning (AI/ML) medical devices, which includes incorporating predetermined change control plans (PCCPs). Speaking at the 2024 Medtech Conference, Marc Lamoureux, manager of the Digital Health Division, highlighted three key challenges in the AI/ML space: algorithmic drift, transparency, and postmarket monitoring. He emphasized that AI/ML models need continuous updates to maintain performance, and transparency is critical for trust and adoption. Health Canada’s draft guidance, released in September 2023, takes a total product lifecycle approach, addressing issues like bias and the need for postmarket monitoring. Regulatory provisions will ensure higher-risk devices are closely monitored. Lamoureux also noted Health Canada is adopting PCCPs, following the lead of the US FDA and Japan’s regulatory agency. The final guidance will be published soon.
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What are the key considerations to help improve trust, access and adoption of AI in #MedTech? #AI is expected to drive significant advancements in medical technology in the coming decade, fundamentally revolutionizing patient care and operational processes. Technologies such as AI-powered diagnostics, personalized treatments, and automation will enhance #healthcare delivery and efficiency, addressing the increasing needs of an aging population and the growing prevalence of chronic diseases. Our latest report, Realizing the value of AI in MedTech within Asia Pacific, developed in collaboration with The Asia Pacific Medical Technology Association (APACMed), explores the immense potential of AI to deliver next-generation, intelligent healthcare that will improve patient outcomes, enhance operational efficiencies, and drive innovation in health technologies, among other benefits. KPMG Taiwan Healthcare & Life Science Service Co-Head Sinney Kuo and Jarret Su has more perspectives to share here: https://bit.ly/3OsdL9i Download the Report (Chinese Edition): https://bit.ly/3ZpRcZm Download the Report (English Edition): https://bit.ly/3Zs3LmZ 【探索AI賦能醫療保健潛力,打造攻守兼備的布局戰略!AI應用層面、注意事項及監管方式,專家來指引】實現亞太區醫療科技領域的AI價值報告 . 🤖在亞太地區,AI應用於醫療領域的潛力巨大,市值估計約2.5億美元!AI如何在醫療科技產業各面向的發展上,發揮關鍵助力、推動產業變革? . 🩺智慧醫療需要醫療智能,負責任的AI治理不容忽視!在實現AI賦能醫療保健生態系統上,需注意哪些地方?亞太各國對AI採用哪些監管方式? . 💡 KPMG安侯建業健康照護與生技產業主持會計師郭欣頤、健康照護與生技產業主持人蘇嘉瑞,帶您深入剖析,並提供獨到見解及重要提醒。 . 《實現亞太區醫療科技領域的AI價值報告》 閱讀精彩內容 👉 https://bit.ly/3OsdL9i 下載中文摘要報告 👉 https://bit.ly/3ZpRcZm 下載英文完整報告 👉 https://bit.ly/3Zs3LmZ . #KPMGTaiwan #亞太區 #智慧醫療 #AI賦能 #監管措施 #連續性照護 #AI存取與應用 #AI網路安全法規
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