Mayo Clinic proceedings. Digital health
Jan 19, 2026
OBJECTIVE: To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incidental pulmonary nodules (IPNs) on chest X-rays (CXRs). PATIENTS AND METHODS: The CREATE (NCT05817110... read more
This study reviews radiographic data segmentation as a cornerstone of machine learning (ML) and deep learning (DL) in dentistry. After outlining artificial intelligence (AI), ML, and DL concepts, it highlights convolutional neural networks-driven tas... read more
The rapid and sensitive detection of trace organic pollutants in water is crucial for ensuring environmental safety. Traditional detection methods struggle to meet the demands of large-scale, real-time, and on-site detection. This paper reviews recen... read more
Lateral flow assays (LFAs) have garnered much interest in the biomedical and agricultural sciences because of their user-friendly design, quick turnaround times, minimal interference, affordability, and ease of use by individuals. To date, many resea... read more
PURPOSE OF REVIEW: Acute heart failure (AHF) is a frequent, high-risk emergency department presentation in which early diagnostic and therapeutic decisions strongly influence outcomes. This review is timely as new evidence is reshaping the first hour... read more
Watershed nitrogen and phosphorus buffering capacity refers to the capacity of a watershed to retain nitrogen and phosphorus in soil, groundwater, and sediments, playing an important regulatory role in balancing human-induced nutrient inputs with dow... read more
Promptable video object segmentation and tracking (VOST) has seen significant advances with the emergence of foundation models like Segment Anything Model 2 (SAM2); however, their application in surgical video analysis remains challenging due to comp... read more
Neural networks : the official journal of the International Neural Network Society
Jan 19, 2026
Image anomaly detection (IAD) usually requires a separated train set to build an inductive model, which then infers on the test set. However, the cost of collecting and labeling training images has inspired zero-shot IAD (ZS-IAD), which directly proc... read more
The American journal of emergency medicine
Jan 19, 2026
PURPOSE: Artificial intelligence systems known as large language models are being evaluated for clinical decision support, yet their role in emergency and primary care remains limited. Physicians in these settings often encounter ear, nose, and throa... read more
Detection of high precision skin lesions, especially melanoma, are still a major challenge in medical imagination due to their close visual equality and lack of reliably labeled datasets. In this study, we introduce a deep learning sketch aimed at ba... read more
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