Latest AI and machine learning research in preventive care for healthcare professionals.
Background Scalable, non invasive tools are critically needed to improve early lung cancer detection and optimize primary care referral pathways. We evaluated Inflammacheck, a point-of-care device utilizing exhaled breath condensate (EBC) H2O2 and physiological parameters with machine learning, for non-invasive lung cancer detection in a real-world screening population. Methods ExPeL study partici...
Abstract Objective To systematically evaluate the diagnostic performance of large language models (LLMs) in automated medical literature screening and to determine their potential role in supporting evidence synthesis workflows. Methods A systematic review and meta-analysis was conducted according to PRISMA DTA guidance. PubMed, Web of Science, Embase, the Cochrane Library and Google Scholar were ...
Automated white blood cell (WBC) classification is essential for leukemia screening but remains challenged by extreme class imbalance, long-tail distr...
Artificial intelligence (AI)-enabled digital interventions, including Generative AI (GenAI) and Human-Centered AI (HCAI), are increasingly used to exp...
Automated white blood cell (WBC) classification is essential for leukemia screening but remains challenged by extreme class imbalance, long-tail distr...
Breast cancer remains a leading cause of cancer-related mortality worldwide. Longitudinal mammography risk prediction models improve multi-year breast...
Accurate monocular depth estimation is critical in colonoscopy for lesion localization and navigation. Foundation models trained on natural images fai...
Background and Objective: Increasing screening volumes, combined with global shortage of radiologists and a high proportion of normal mammograms, chal...
The automatic identification of cough segments in audio through the determination of start and end points is pivotal to building scalable screening to...
Background Sickle cell disease (SCD) is a common inherited genetic disorder and contributor to global childhood mortality and morbidity. In the Democr...
Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnormality associated with increased mortality in esta...
Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environme...
Background and aims Population screening for liver disease in high-risk groups is recommended. Community diagnosis of liver disease is a challenge due...
Accurate polyp segmentation from colonoscopy images is critical for colorectal cancer prevention, yet the generalization of deep learning models under...
Abstract Background: Systematic reviews (SRs) are essential for evidence-based medicine but require extensive time and resources for abstract screenin...
Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during colonoscopy. However, the variability in appearanc...
Background: Cognitive decline and dementia represent major public health challenges in aging populations. Natural language processing (NLP)-augmented ...
Early screening for glaucoma and diabetic retinopathy (DR) is critical to prevent irreversible vision loss, yet remains inaccessible to many underserv...
Large language models (LLMs) are increasingly used by the public to seek health information, yet their reliability in addressing common vaccine myths ...
Mapping of T cell receptors (TCRs) to their cognate MHC-presented peptides (pMHC) is central for the development of precision immunotherapies and vacc...