Long COVID poses a significant disease burden globally, but its heterogeneous presentation and unreliable coding practices render it difficult to study. Developing efficient phenotyping algorithms is crucial to enabling risk prediction and effective management…
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Subspecialty knowledge barriers have limited the adoption of large language models (LLMs) in oncology. We introduce Woollie, an open-source, oncology-specific LLM trained on real-world data from Memorial Sloan Kettering Cancer Center (MSK) across lung,…
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Numerous Google Cloud services, including those used widely within healthcare, such as Google Vertex AI Online Prediction, Dialogflow CX, Agent Assist and Contact Center AI, were down for nearly four hours on Thursday affecting…
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Thalassemia is an inherited blood disorder. Current diagnostic methods mainly rely on sophisticated equipment and specifically trained technicians. This study aims to identify and genotype thalassemia by applying machine learning (ML) algorithms to routine…
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Revolutionary FDA Approval Marks Medical Milestone
Startup Clairity has achieved a groundbreaking milestone in healthcare technology, securing FDA approval for the agency’s first artificial intelligence tool specifically designed to predict five-year breast cancer risk from…
Ultrasound assessment of fetal size and growth is the mainstay of monitoring fetal well-being during pregnancy, as being small for gestational age (SGA) or large for gestational age (LGA) poses significant risks for both…
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The National Heart Centre Singapore is set to pilot a new AI-powered solution for rapid coronary artery disease prediction.SENSE (Singapore Heart Lesion Analyser) is a machine learning-driven system that can automatically interpret heart image scans…
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The complexities inherent in EHR data create discrepancies between real-world evidence and RCTs, posing substantial challenges in determining whether a treatment is likely to have a beneficial impact compared to the standard of care…
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Accurate prediction of prognosis and postoperative radiotherapy response is critical for personalized treatment in head and neck squamous cell carcinoma (HNSCC). We developed a multimodal deep learning model (MDLM) integrating computed tomography, whole-slide images,…
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Determining tumor microsatellite status has significant clinical value because tumors that are microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) respond well to immune checkpoint inhibitors (ICIs) and oftentimes not to chemotherapeutics. We propose…
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