Current self-supervised learning (SSL) methods for 3D medical imaging rely on simple pretext formulations and organ- or modality-specific datasets, limiting their generalizability and scalability. We present 3DINO, a cutting-edge SSL method adapted to 3D…
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Cardiovascular diseases remain the leading cause of death in developed countries. This study introduces deep learning ensembles for arrhythmia detection and atrial fibrillation (AF) recurrence prediction from electrocardiogram scans, supported by explainable artificial intelligence…
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Biased and poorly documented dermatology datasets pose risks to the development of safe and generalizable artificial intelligence (AI) tools. We created a Dataset Nutrition Label (DNL) for multiple dermatology datasets to support transparent and…
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Ed Gaudet, CEO and Founder of Censinet
Artificial intelligence (AI) is the ultimate double-edged sword in healthcare. On one side, AI is already driving real improvements, from accelerating diagnostic imaging to streamlining operational workflows such…
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What You Should Know:
–Flatiron Health, a leading healthtech company dedicated to improving cancer care and advancing research using real-world data, today announced the launch of six new hematology Panoramic datasets, representing another critical moment…
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What You Should Know:
– Caravel Bio, the first joint platform for protein discovery and delivery that enables new applications of synthetic biology, today announces its selection for a $7.8M award from the U.S. National Science…
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Continuous prediction of glucose levels and hypoglycemia events is critical for managing type 1 diabetes mellitus (T1DM) under intensive insulin therapy. Existing models focus on a single task, limiting their practicality and adaptability in…
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Data analytics stands as the foundation that supports individualised patient treatment while maximising operational capabilities and business development potential by using strategic resource distributions and analytic insights. Healthcare organisations collect enormous datasets from four…
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Recent advances in unbiased metagenomic next-generation sequencing (mNGS) enable simultaneous examination of microbial and host genetic material. We developed a multimodal machine learning-based diagnostic approach to differentiate lung cancer and pulmonary infections by analyzing…
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Remote photoplethysmography (rPPG) is gaining traction for non-contact heart rate estimation, yet most publicly available datasets are demographically biased. In this study, we analyze 100 rPPG studies, providing the first quantitative cross-model audit of…
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