Latest AI and machine learning research in product alert for healthcare professionals.
Black-box models limit the adoption of artificial intelligence in medicine due to their lack of interpretability and reproducibility. We introduce a statistically grounded framework that provides fully interpretable, rule-based clinical classification using the Bernoulli Naïve Bayes (BNB) model. The method applies supervised $χ^2$-guided statistical binarization to continuous variables, identifyin...
The cost of healthcare remains a concern in the United States and may have been influenced by disruptions associated with the COVID-19 pandemic. This study examines healthcare financial vulnerability before and after the pandemic using Medical Expenditure Panel Survey (MEPS) data from 2019 and 2021. High financial burden was defined as out-of-pocket healthcare expenditures exceeding 10% of family ...
Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at diff...
Chest radiograph datasets often combine multiple images with Clinical Indication, Findings, and Impression, although these inputs are produced at diff...
Visual place recognition (VPR) is a key enabler of accurate localization and long-term autonomous navigation in robotics applications, such as loop cl...
Visual place recognition (VPR) is a key enabler of accurate localization and long-term autonomous navigation in robotics applications, such as loop cl...
Limited-angle digital breast tomosynthesis (DBT) reconstructs a volume from a few low-dose projections over a narrow arc. At a representative nine-vie...
_ SURPASS-HF: Safety and Utility of Remote Pulmonary Artery Sensor Shared-management in Heart Failure --Background-- Insulin-dependent diabetics self-...
Aphasia following stroke commonly produces systematic naming errors with characteristic profiles, but whether general-purpose language models not desi...
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 ...
Humans make emotional facial expressions and have a cardiac response when they catch themselves in a mistake or receive feedback about task performanc...
Symbolic regression (SR) discovers analytical equations from data, yielding glass-box models with directly interpretable formulas, unlike black-box me...
Accurate interpretation of planar ventilation-perfusion (V/Q) scintigraphy, used for diagnosing pulmonary embolism (PE) based on PIOPED/EANM guideline...
Abstract Climate change is altering environmental conditions that influence foodborne disease transmission, yet traditional systematic reviews cannot ...
The Internal Waves Service screens the Sentinel-1 Wave-mode archive for internal solitary waves, routing detections to experts whose adjudication time...
Three audiences -- the family of a newly diagnosed Ewing sarcoma patient, the long-term survivor, and the cooperative-group trial statistician -- rece...
- Objective: Multimodal deep learning models in oncology are currently limited by monolithic designs that rigidly couple data ingestion, clinical rout...
When randomized controlled trials are infeasible, researchers may leverage natural experiments for causal inference. Interrupted time-series (ITS) des...
Accurate prediction of patient-specific therapeutic response from pre-treatment transcriptomes is hindered by the scarcity of matched clinical respons...
Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining. Ho...