AIMC Topic: Machine Learning

Clear Filters Showing 2841 to 2850 of 34417 articles

Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.

Ecotoxicology and environmental safety
Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing significant risks to human health. Despite their low environmental concentrations, dioxins accumulate in tissues, particularly in top predators and humans, r...

Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example.

Environment international
Continuous Emission Monitoring Systems (CEMS) are critical for real-time pollutant measurement, widely deployed to supervise industrial emissions and ensure regulatory compliance. Despite their utility, CEMS data face challenges of data fabrications,...

Comparative analysis of AI algorithms on real medical data for chronic pain detection.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Chronic pain is a pervasive healthcare challenge with profound implications for patient well-being, clinical decision-making, and resource allocation. Traditional detection methods often rely on subjective assessments and ma...

A miniaturized liver function detection system with machine learning enhancing strategy.

Biosensors & bioelectronics
Serum alanine aminotransferase (ALT) is one of the most sensitive indicators of liver function and is crucial in diagnosing acute liver injury (ALI). However, its widespread clinical application is limited due to expensive equipment, detection delays...

Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors.

Acta pharmacologica Sinica
GluN3A-containing NMDA receptors have recently emerged as promising therapeutic targets for neurological disorders. However, discovering potent modulators remains a significant challenge, primarily due to the limitations of traditional high-throughpu...

Diagnosis melanoma with artificial intelligence systems: A meta-analysis study and systematic review.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: One of the most promising and rapidly advancing research areas in recent years is using dermoscopic images for automatic diagnosis with artificial intelligence and machine learning methods.

An approach in developing graphical feature maps derived from machine learning and its application in loquat juice classification.

Food chemistry
This study introduces a new methodology for developing graphical feature maps using weighted artificial neural networks (w-ANNs) and demonstrates its application in the classification of loquat juice varieties (namely loquat_baisha and loquat_hongsha...

Dual energy CT-based Radiomics for identification of myocardial focal scar and artificial beam-hardening.

International journal of cardiology
BACKGROUND: Computed tomography is an inadequate method for detecting myocardial focal scar (MFS) due to its moderate density resolution, which is insufficient for distinguishing MFS from artificial beam-hardening (BH). Virtual monochromatic images (...

Plasma proteomic profiles for early detection and risk stratification of non-small cell lung carcinoma: A prospective cohort study with 52,913 participants.

International journal of cancer
Early detection of non-small cell lung cancer (NSCLC) can improve survival rates, and plasma proteomics may provide effective tools for risk prediction. The population for this study included 52,913 participants and 2911 plasma proteomics from UK Bio...

An EEG-based imagined speech recognition using CSP-TP feature fusion for enhanced BCI communication.

Behavioural brain research
BACKGROUND: Imagined speech has emerged as a promising paradigm for intuitive control of brain-computer interface (BCI)-based communication systems, providing a means of communication for individuals with severe brain disabilities. In this work, a no...