IntelliSOFT Consulting Ltd’s Post

At Deep Space Biology, we recognize the profound potential of Large Language Models (LLMs) to revolutionize healthcare through enhanced data analysis and decision support. However, we must not overlook the ethical concerns surrounding fairness, bias, transparency, and privacy. As pioneers in the intersection of AI, space and biotechnology, we emphasize the critical need for well-defined ethical guidelines and continuous human involvement. Only by addressing these ethical challenges head-on can we fully harness the benefits of LLMs while ensuring they serve all communities equitably and responsibly. Since the release of ChatGPT in 2022, Large Language Models (LLMs) have shown great promise in healthcare, enhancing clinical decision-making, diagnosis, and patient communication. However, these advancements come with ethical concerns such as the spread of inaccurate medical information, privacy breaches, and biases related to gender, culture, or race. Despite these issues, comprehensive studies addressing the ethical challenges of LLMs in healthcare are lacking. To address this gap, researchers conducted a systematic review to map the ethical landscape of LLMs in healthcare, identifying potential benefits and harms. https://lnkd.in/d7N8bjNZ By Priyanjana Pramanik MSc. Reviewed by Lily Ramsey News Medical #HealthcareInnovation #AI #Bioinformatics #EthicalAI #PatientSafety #DataTransparency #FairnessInAI #DeepSpaceBiology #ClinicalDecisionSupport #LLMs #HealthcareEthics #ResponsibleAI #FutureOfHealthcare #MedicalAI #DataPrivacy

In the event your algorithm missed Part IV of my five-part series on AI in Healthcare, I am reposting this one more time. ⚡ If you're already a subscriber, you've likely read part V, which went out on Sunday. If you haven't subscribed yet, what are you waiting for? 😕 Part IV probes the question, do we truly understand the capabilities of AI? 😶🌫️ Please chime in with your thoughts! 🤔 Citations: Quanta Magazine Scientific American TechRadar Pro U.S. Department of Homeland Security Axios STAT U.S. Department of Health and Human Services (HHS) Joel Bervell The San Francisco Standard Forbes Tristan Harris Center for Humane Technology #AI #HEALTHtEQUITY #HealthEquity #healthcare #machinelearning #generativeAI #medicalscribes #digitalhealth #digitalhealthequity #womeninmedicine #DEI #digitaldeterminantsofhealth #SDOH

Happening this week: Join us for the Penn LDI conference, (Re)Writing the Future of Health Care With Generative AI! Discover how #AI is transforming clinical care and patient communication. 🤖 Learn more and register here: https://lnkd.in/epDHipiG

GenAI in Chinese Healthcare China is leveraging AI, particularly large language models (LLMs), to enhance its primary healthcare system. Recent studies demonstrate LLMs' potential to improve both clinical competency and patient-provider communication in primary care settings. However, these innovations have primarily been tested in well-resourced urban areas, raising questions about their applicability in underserved regions. While AI shows promise, experts emphasize that technology alone cannot solve all primary healthcare challenges. Systemic changes, including provider incentives, community outreach, and clear policies on technology financing and regulation, are crucial. Further research is needed to assess LLMs' effectiveness in low-resource settings and their potential to address healthcare inequities. Read more at https://lnkd.in/gSUvcEZh - Amol Deshmukh| aud3@cornell.edu #artificialintelligence #workplaceAI #technology #work #labor #innovation #workplace #automation #neuralnetworks #LLMs #LargeLanguageModels #nlp #business #tech #law #legal #labor #workforce #ethics #aigovernance #healthcare #education

Revolutionizing Healthcare: AI's Impact on Diagnostic Capability and Ethnic Communities Discover how AI-powered language models have transformed the healthcare industry. Explore the application of AI in enhancing diagnostic capabilities and improving healthcare delivery in ethnic communities with language barriers. #AIinHealthcare #DiagnosticCapability #HealthcareInnovation #EthnicCommunities #LanguageBarriers #HealthcareTechnology #AIAdvancements #TransformingHealthcare #MedicalAI #HealthEquity

The article discusses the transformative potential of #ArtificialIntelligence (AI) in enhancing #Healthcare outcomes in #LowIncomeCountries. It emphasizes the importance of creating reliable, valid, and fair algorithms to reduce bias and ensure effectiveness. Highlighted are the roles of global organizations like UNESCO, WHO, and the European Union in promoting ethical AI use, alongside the need for philanthropic support in research for AI guidelines considering marginalized populations. Collaboration among governments, international bodies, researchers, and industry leaders is deemed crucial for the responsible adoption of AI in healthcare. Marilyn Murrillo Romuladus Emeka Azuine, DrPH, MPH, RN Magnus Azuine, PhD, MPH, MSc, CHAS https://lnkd.in/dPsShKN9

🎯 Artificial Intelligence, Taylor Swift and the US Presidential debate ⚠️ these are my thoughts - TLDR: responsible AI based on data integrity, privacy and accuracy is key in building trust in both clinicians and patients/users/communities. The recent U.S. presidential debate spotlighted #artificialintelligence as a critical issue. Taylor Swift was even “pushed” to voice her concerns about the potential for AI to spread #misinformation. As AI continues to reshape industries, these fears are particularly relevant in healthcare. 🫀 In medicine, accuracy of #data and truth of evidence are paramount. AI has immense potential to revolutionize clinical decision-making, enhance patient #care, and address longstanding #inequities, but it also raises critical questions: • 𝗗𝗮𝘁𝗮 𝗽𝗿𝗶𝘃𝗮𝗰𝘆: How can we safeguard sensitive health data from misuse or manipulation? • 𝗠𝗶𝘀𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: If AI can distort facts, how do we prevent false or biased medical recommendations from influencing patient outcomes? • 𝗛𝗲𝗮𝗹𝘁𝗵 𝗲𝗾𝘂𝗶𝘁𝘆: How do we ensure AI helps bridge, not widen, disparities in care? 🔹Last year, our team presented our research at the #EACVI Congress in Barcelona, where we demonstrated AI’s potential to close race-based disparities in the timely management of severe aortic stenosis (AS) and mitral regurgitation (MR). We implemented a natural language processing (NLP) clinical decision support algorithm that automatically identifies severe AS/MR from #echocardiographic reports. It then sends a nudging notification to the referring clinician, recommending referral to the hospital’s Structural Heart Valve clinic. ❓The result? Improved access to timely, life-saving interventions for all patients, regardless of race. #AI is a powerful tool, but with great power comes great responsibility. How we implement it in #healthcare—ensuring trust, equity, and ethical oversight—will define its true impact. ⬇️📱Would love your thoughts on how we can leverage AI responsibly for a better, more equitable future in healthcare. #AIinHealthcare #DataPrivacy #HealthEquity #HealthcareInnovation #EthicalAI #medicine #cardiology #science #bioethics #trust #TaylorSwift

Stanford University recently released an interesting set of research showcasing how it has been making significant strides in exploring the applications of AI within psychotherapy. The research shows that there is immense potential for large language models (LLMs) to augment and even automate parts of the therapeutic process, such as note-taking and delivering therapy. However, the university also emphasizes the complexity and high stakes involved in psychotherapy, highlighting the need for cautious and responsible integration of AI. How to do this effectively is the essential question to answer today. Any process for evaluating AI readiness in clinical settings must focus on safety, confidentiality, equity, effectiveness, and implementation, ensuring that these technologies can truly benefit patients without compromising ethical standards. Our organization has focused deeply on understanding the responsible use of AI in various high-stakes environments, including government work. Our experience with 5G, telecom, Internet of Things, Digital Twin technologies and incorporating AI within those sectors demands that we understand the importance of robust security measures, data privacy, and transparency where one mistake can result in a catastrophe. For example, the recent Mirai botnet attack exploited IoT devices to launch massive DDoS attacks, highlighting the critical need for stringent security protocols MIMO is intimately familiar with. These principles are directly applicable to the integration of AI in psychotherapy. By ensuring that AI systems are secure, private, and transparent, we can help mitigate the risks associated with their use in mental health care, potentially improving accessibility and personalized treatment options for patients. Implementing techniques such as end-to-end encryption, federated learning, and zero-trust architectures can significantly enhance the security and privacy of AI systems in this sensitive domain. We believe that the government can play a pivotal role in shaping the future of AI in psychotherapy by collaborating with industry partners to ensure ethical and effective integration of AI technologies. Through public-private partnerships, the government can help develop standardized guidelines, secure data-sharing frameworks, and regulatory compliance to protect patient privacy and promote transparency. These collaborations can facilitate research on unbiased, personalized AI models and establish robust security measures, ultimately enhancing the accessibility and quality of mental health care services for the public. Thanks to Chris Kraft to share these resources. https://lnkd.in/e72N_rgx

🌟 Exciting Developments in AI & Healthcare 🌟 In our continuous journey towards innovation, we're witnessing the integration of technologies that challenge our understanding and push the boundaries of possibility. The advent of advanced large language models exemplifies this shift, showcasing an extraordinary breadth of capabilities - from enhancing our culinary experiences to advancing medical diagnostics. I find the rapid evolution of these technologies both exhilarating and thought-provoking. These models have transitioned from nascent tools to sophisticated systems capable of outperforming medical students in U.S. licensing exams within a mere three years. Their proficiency now spans texts, images, videos, sounds, and even molecular structures, transforming our approach to medicine and research.... The acceleration of AI capabilities brings to light the imperative need to address the emerging challenges they pose - from ethical dilemmas to the risk of misinformation. The recent RAISE (Responsible AI for Social and Ethical Healthcare) meeting, which saw experts from across the globe converge to discuss these topics, marks a significant step towards this goal. As we continue to explore the vast potential of AI in healthcare, we must remain vigilant and collaborative in our efforts to harness its benefits responsibly. I highly recommend reading the editorial “Policy in Progress — The Race to Frame AI in Health Care” by Isaac Kohane, MD, PhD, for an insightful exploration of these themes and the future of AI in healthcare: https://nejm.ai/48wIYQ9 #AIinHealthcare #Innovation #EthicalAI #DigitalHealth

Are we ready for #GenAI therapists? The Stanford Institute for Human-Centered Artificial Intelligence (HAI) looks into it. More detailed research reports here: 🔹Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation https://lnkd.in/efhrukfc 🔹Readiness for AI Deployment and Implementation (READI): A Proposed Framework for the Evaluation of AI-Mental Health Applications https://lnkd.in/eKX9rmHi