Deep learning techniques have significantly enhanced the convenience and precision of ultrasound image diagnosis, particularly in the crucial step of lesion segmentation. However, recent studies reveal that both train-from-scratch models and pre-trained models often…
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Federated learning (FL) enables collaborative analysis of decentralized medical data while preserving patient privacy. However, the covariate shift from demographic and clinical differences can reduce model generalizability. We propose FedWeight, a novel FL framework…
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Neuropathic corneal pain (NCP) is an underdiagnosed ocular disorder caused by aberrant nociception and hypersensitivity of corneal nerves, often resulting in chronic pain and discomfort even in the absence of noxious stimuli. Recently, microneuromas…
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What You Should Know:
– Veradigm, a provider of healthcare data and technology solutions, today announced a significant advancement in the application of artificial intelligence (AI) to scale the generation of real-world evidence (RWE) for…
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Accurate medical decision-making is critical for both patients and clinicians. Patients often struggle to interpret their symptoms, determine their severity, and select the right specialist. Simultaneously, clinicians face challenges in integrating complex patient data…
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Verily, Alphabet’s health data and AI subsidiary, has been awarded a $14.7 million research grant from the Michael J. Fox Foundation (MJFF) for Parkinson’s research to generate a detailed molecular dataset of Parkinson’s disease.The…
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Groundbreaking Medical Imaging Resource
Harvard Medical School’s Rajpurkar Lab and Gradient Health have unveiled ReXGradient-160K, marking a historic milestone in medical artificial intelligence research. This revolutionary chest X-ray collection stands as the world’s largest publicly…
This study proposes a semi-weakly supervised learning approach for pulmonary embolism (PE) detection on CT pulmonary angiography (CTPA) to alleviate the resource-intensive burden of exhaustive medical image annotation. Attention-based CNN-RNN models were trained on…
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Despite significant advances, the prevention and management of cardiovascular disease remain challenging, especially for ischemic heart disease (IHD). Current clinical decision-making relies heavily on physician expertise, guideline-directed therapies, and static risk scores, which often…
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Cardiotocography (CTG) is essential for monitoring high-risk pregnancies, yet perinatal asphyxia prediction accuracy remains limited to 50–55%. Regions of artifacts (missing valid signals)-including signal processing aberrations-possibly contribute to this limitation, highlighted by 40% of…
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