Latest AI and machine learning research in refractive surgery for healthcare professionals.
Background: Post-stroke dysphagia (PSD) contributes to aspiration, pneumonia, malnutrition, prolonged hospitalization and mortality. We evaluated the discrimination, validity and readiness of machine learning and data-driven prediction models for PSD-related outcomes. Methods: Following a prospectively registered protocol (PROSPERO CRD420261419259), we searched PubMed/MEDLINE, Embase, Web of Scien...
Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at different stages of care. We evaluated 15,000 ReXGradient-160K studies with two readable images and five CheXbert-derived report observations. Frozen DenseNet-121 and Bio+ClinicalBERT encoders were used to compare image-only, Indication-only, fixed-order...
Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at diff...
When a large disaster strikes, responders need a map of which buildings are damaged within hours. The models that do well on public benchmarks assume ...
Cancer genomics and diagnostics is a rapidly evolving field in which identifying which topics attract early citation prominence can inform laboratory ...
Error monitoring allows for detecting mistakes and adapting behavior. Error monitoring is associated with increased theta (4-7 Hz) EEG activity record...
Reliable confidence estimates are essential in semantic segmentation, especially in safety-critical settings where overconfident errors can mislead do...
Background: Postoperative delirium (POD) is a complication associated with most types of surgery, and is associated with a number of detrimental effec...
Vision loss compromises the quality of life of millions of people worldwide. Currently, vision-restoring therapies are lacking. Post-mortem preservati...
Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that a...
Medical device recalls are a critical regulatory mechanism for protecting patient safety. The growing volume of FDA recall records presents challenges...
Short-form video platforms increasingly shape how young audiences encounter health information. Generative artificial intelligence can produce standar...
Curvilinear object segmentation, including vessels and cracks, is challenging due to extreme spatial sparsity and topological fragility, where small l...
The clinical and molecular heterogeneity observed in amyotrophic lateral sclerosis (ALS) presents a challenge for diagnosis, prognosis, and treatment....
Abstract Purpose Radiologic surveillance is essential for oropharyngeal cancer (OPC) survivors, guiding recurrence detection and follow-up strategies....
Reinforcement learning (RL) post-training of Diffusion Transformers (DiTs) is prohibitively expensive, requiring thousands of high-end GPUs. Existing ...
Scientific reasoning models for biology combine language models with foundation models trained on multimodal biological data, including DNA, RNA, and ...
Patients diagnosed with type 2 diabetes (T2D) are at increased risk of developing cardiovascular disease (CVD), the leading cause of morbidity and mor...
There is interest in the use of recent single-cell spatial transcriptomic technologies to gain biological insights into disease mechanisms. Previously...
Decision-relevant building damage assessment is critical for prioritizing resources and recovery after a disaster, yet most automated methods either f...