Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 60,001 to 60,010 of 228,014 articles

Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.

Mayo Clinic proceedings. Digital health
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 

Radiographic Data Segmentation as a Tool in Machine Learning and Deep Learning Artificial Intelligence Algorithms.

Dental clinics of North America
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 

Advances and innovations in machine learning-based spectral detection methods for trace organic pollutants.

The Analyst
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 

Progress of lateral flow assays for the detection of molecular and microbial species: from basic formats to microfluids, CRISPR and artificial intelligence.

The Analyst
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 

Early management of acute heart failure.

Current opinion in critical care
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 

Data-driven assessment of nitrogen and phosphorus buffering capacity across 460 Chinese watersheds: Spatial patterns, drivers, and future projections.

Water research
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 

TSMS-SAM2: Multi-scale Temporal Sampling Augmentation and Memory-Splitting Pruning for Promptable Video Object Segmentation and Tracking in Surgical Scenarios.

Machine learning. Health
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 

SCAD: A self-constrained solution to automate context-guided zero-shot image anomaly detection.

Neural networks : the official journal of the International Neural Network Society
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 

Empowering front-line physicians with AI: Evaluating large language models in everyday ENT care.

The American journal of emergency medicine
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 

Developing a trustworthy and explainable framework for classifying skin lesions through transfer learning and attention mechanisms.

Computational biology and chemistry
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