Integrating Large Language Models (LLMs) into healthcare promises substantial advancements but requires careful consideration of technical, ethical, and regulatory challenges. Closed LLMs of private companies offer ease of deployment but pose risks related to…
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Partnerships between public and private organizations in digital health can promote more accessible, affordable, and high-quality care, but they also raise ethical and governance challenges. We searched PubMed, EMBASE, and Web of Science, identifying…
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The Current State of Healthcare Data Privacy
The Sequoia Project’s Privacy and Consent Workgroup has conducted an extensive review of existing consent models and frameworks. Their goal: achieving “computable consent” – an automated system where…
The MedTech industry is accelerating at an unprecedented pace. As AI reshapes the landscape, global collaborations are expanding, and the regulatory frameworks are evolving to meet new challenges. Here are ten global MedTech trends…
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Qualified Health, a public benefit corporation that provides the infrastructure for generative AI in healthcare, has launched with $30 million in seed funding.The funding round was led by SignalFire, Healthier Capital, Town Hall Ventures,…
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Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. Generative Adversarial Networks (GANs) have been employed for this purpose, but their…
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News
The House Task Force on Artificial Intelligence publishes its findings and recommendations, which include:
Challenges include data availability and quality, incomplete or inaccurate responses, non-individualized recommendations, lack of decision transparency, data privacy, interoperability with existing…
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The business world was roiled earlier this year when a finance worker in Hong Kong was duped into handing over $25.6 million (200 million Hong Kong Dollars) after he joined a video call that…
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Robust data privacy regulations hinder the exchange of healthcare data among institutions, crucial for global insights and developing generalised clinical models. Federated learning (FL) is ideal for training global models using datasets from different…
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Security concerns and vendor restrictions are some of the major barriers to unlocking health data’s full potential in raising patient outcomes.In the HIMSS24 APAC plenary session, “Power of Data in Modern Healthcare,” Cho Chi-Heum, professor…
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