What You Should Know
– Eli Lilly and Company has entered a strategic collaboration with Chai Discovery to deploy frontier AI for the design of novel biologic therapeutics.
– The partnership includes the development of an…
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If you’ve ever felt like “one big AI” can’t possibly handle the complexity of healthcare, you’re not alone. Clinical work moves in too many directions for a single model to reliably keep up.In this…
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OpenAI’s Strategic Acquisition
OpenAI Group PBC has announced its acquisition of Neptune Labs Inc., a Poland-based startup specializing in AI model optimization and development tools. The announcement marks another significant move in OpenAI’s expansion strategy,…
Missed periodontitis diagnoses are common, and AI dental radiography systems based on clinical standards can enhance reliable detection. We introduce and evaluate HC-Net+, a deep-learning model that mimics clinical pathways while integrating localized tooth…
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Nicole Ventrone, Partner at Beghou
Pharma is embracing GPT-5, shifting AI from chatbot to enterprise agent as it accelerates productivity amid regulatory challenges.
Large pharmaceutical and biotech companies have spent the last couple of years running…
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Patients with clear cell renal cell carcinoma (ccRCC) face a high risk of recurrence after surgery, but existing clinical tools based on clinicopathological factors or costly molecular profiling often lack precision and clinical feasibility….
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Large language models (LLMs) used by English local authorities to support social workers may be introducing gender bias into care decisions, according to research from London School of Economics and Political Science (LSE).
The study,…
The Med-Gemini Mistake Discovery
Google’s ambitious healthcare AI model, Med-Gemini, recently came under scrutiny when a significant error was discovered in both a 2024 research paper and accompanying blog post. The mistake involved referencing “basilar…
Credit: Campanella, et al., Nature Medicine
What You Should Know:
– A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence…
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Traditional tuberculosis (TB) screening involves radiologists manually reviewing chest X-rays (CXR), which is time-consuming, error-prone, and limited by workforce shortages. Our AI model, AIRIS-TB (AI Radiology In Screening TB), aims to address these challenges…
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