Artificial Intelligence Medical Compendium

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

Showing 1,201 to 1,210 of 163,745 articles

Machine Learning-Driven SERS Analysis Platform for Accurate and Rapid Diagnosis of Peritoneal Metastasis from Gastric Cancer.

Annals of surgical oncology Jul 26, 2025
BACKGROUND: Peritoneal metastasis (PM) is the most common form of distant metastasis in gastric cancer and is a major cause of mortality. Current diagnostic approaches suffer from low sensitivity, time-consuming procedures, and cannot provide real-ti... read more 

Transforming label-efficient decoding of healthcare wearables with self-supervised learning and "embedded" medical domain expertise.

Communications engineering Jul 26, 2025
Healthcare wearables are transforming health monitoring, generating vast and complex data in everyday free-living environments. While supervised deep learning has enabled tremendous advances in interpreting such data, it remains heavily dependent on ... read more 

Smartphone-derived optical proxies for estimating toxicity risk of Microcystis aeruginosa complex in inland waters.

Environmental monitoring and assessment Jul 26, 2025
Toxic blooms dominated by cyanobacterial colonies of Microcystis aeruginosa complex (MAC) accumulate in the water surface, so they can be tracked by remote sensing. The abundance of toxic MAC cells is related to colony size, a parameter affecting wat... read more 

External validation of a motion capture-based surgical skill assessment system in laparoscopic simulation training environments.

Surgical endoscopy Jul 26, 2025
PURPOSE: To externally validate our surgical skill assessment system, which provides comprehensive real-time feedback based on motion capture (Mocap) metrics of laparoscopic instruments in simulation training environments. read more 

A classification method for fluorescence emission spectra of anionic surfactants with few-shot learning.

Journal of molecular modeling Jul 26, 2025
CONTEXT: The unregulated use of anionic surfactants poses significant environmental risks, necessitating methods for their rapid and accurate identification. While fluorescence spectroscopy is a powerful tool, its application faces a critical challen... read more 

A machine learning optimized Dielectric Ultra-focused Oscillatory (DUO) electrode for low temperature electrosurgery.

Scientific reports Jul 26, 2025
The widespread adoption of radio frequency (RF) energy has made electrosurgery a cornerstone of modern surgical procedures, primarily due to its ability to minimize blood loss during, or independent of, tissue incision. Among the various electrosurgi... read more 

Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin.

Scientific reports Jul 26, 2025
Accurate river discharge forecasting is essential for effective water resource management, particularly in regions prone to monsoonal variability and extreme weather events. This study presents an interpretable deep learning framework for daily river... read more 

Insurance claims estimation and fraud detection with optimized deep learning techniques.

Scientific reports Jul 26, 2025
Estimation and fraud detection in the case of insurance claims play a cardinal role in the insurance sector. With accurate estimation of insurance claims, insurers can have good risk perceptions and disburse compensation within proper time, while fra... read more 

Hybrid modeling for optimizing electrospun polyurethane nanofibrous membranes in air filtration applications.

Scientific reports Jul 26, 2025
Nanofibers have gained recognition as promising materials for air filtration due to their high surface area-to-volume ratio, adjustable porosity, and exceptional mechanical properties. However, optimizing their structural characteristics to maximize ... read more 

Multi-cohort machine learning identifies predictors of cognitive impairment in Parkinson's disease.

NPJ digital medicine Jul 26, 2025
Cognitive impairment is a frequent complication of Parkinson's disease (PD), affecting up to half of newly diagnosed patients. To improve early detection and risk assessment, we developed machine learning models using clinical data from three indepen... read more 
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