Rapid advances in large language models (LLMs) are transforming the role of students and principal investigators (PIs) in biomedical research. This perspective examines how LLMs can reshape the laboratory model as de facto “Co-PIs”…
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Pathologic myopia is a leading cause of visual impairment and blindness. While deep learning-based approaches aid in recognizing pathologic myopia using color fundus photography, they often rely on implicit patterns that lack clinical interpretability….
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Accurate and comprehensive interpretation of pulmonary embolism (PE) from Computed Tomography Pulmonary Angiography (CTPA) scans remains a clinical challenge due to the limited specificity and structure of existing AI tools. We propose an agent-based…
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We introduce a framework to adapt large language models for medicine: (1) Modeling: breaking down medical workflows into manageable steps; (2) Optimization: optimizing model performance via advanced adaptations; and (3) System engineering: developing agent…
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In healthcare, federated learning (FL) is emerging as a methodology to enable the analysis of large and disparate datasets while allowing custodians to retain sovereignty. While FL minimises data-sharing challenges, concerns surrounding ethics, privacy,…
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Medical image segmentation is vital for accurate diagnosis. While U-Net-based models are effective, they struggle to capture long-range dependencies in complex anatomy. We propose GH-UNet, a Group-wise Hybrid Convolution-ViT model within the U-Net framework,…
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A critical gap in the adoption of large language models for AI-assisted clinical decisions is the lack of a standardized audit framework to evaluate models for accuracy and bias. Our framework introduces a five-step…
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Sebaceous gland carcinoma (SGC) and some poorly differentiated squamous cell carcinomas (SC) of the eyelid may have overlapping clinical and histopathologic features, leading to potential misdiagnosis and delayed treatment. The authors developed a deep…
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Alzheimer’s Disease and Related Dementias (ADRD) pose a major public health challenge, with a critical need for accurate and scalable tools for detecting cognitive impairment (CI). Readily available electronic health records (EHRs) contain valuable…
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Northwell Health is broadening its use of a suite of safety and security technologies designed to keep its employees and patients safe network-wide. WHY IT MATTERSWorking with Motorola Solutions, the New York health system is…
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