Artificial Intelligence Medical Compendium

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

Showing 26,371 to 26,380 of 218,283 articles

Attentional Avoidance of Sexual Cues in Psychogenic Erectile Dysfunction: An Eye-Tracking and Machine Learning Study.

Andrology
BACKGROUND: Psychogenic erectile dysfunction (pED) is a prevalent male erectile dysfunction without organic causes, and difficulties in erection attainment and post-penetration maintenance often co-occur. Although neuroimaging studies have implicated... read more 

Identifying cathepsin B as a key regulator of programmed cell death in acute pancreatitis.

International immunopharmacology
Acute pancreatitis (AP) lacks effective therapies, and excessive programmed cell death (PCD) drives its pathogenesis. This study identified cathepsin B (CTSB) as a core PCD regulator in AP via bioinformatics and animal experiments. Gene Expression Om... read more 

Development and Validation of AI System for Tooth Detection and Diagnosis in Dental Radiographs.

International dental journal
INTRODUCTION AND AIMS: To develop and validate an AI-automated system for dental charting that accounts for multiple radiograph types and younger patients. METHODS: A total of 3705 dental radiographs were collected in Slovakia and Egypt between 2023 ... read more 

Generative artificial intelligence use in medical research: A medical student vs. physician survey from Saudi Arabia.

International journal of medical informatics
INTRODUCTION: Generative artificial intelligence (GenAI) such as ChatGPT, is increasingly used to generate research ideas, aid in literature reviews, and support clinical reasoning. While its adoption is rapidly growing worldwide, concerns persist re... read more 

Biomarker-anchored screening of dietary microplastics via a gut microbiota-informed machine learning model.

Journal of hazardous materials
Microplastics (MPs) are increasingly recognized as emerging contaminants in the human diet, yet the absence of unified biomarker-anchored screening thresholds hampers quantitative risk assessment. This study establishes a gut microbiota-anchored mach... read more 

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

NPJ precision oncology
Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apoptotic cell death and senescence pathways contribute to tumor evolution and immunosuppression, their in... read more 

Integrating microbial bioremediation, multi-omics, and emerging technologies for polycyclic aromatic hydrocarbon (PAHs) detoxification.

Journal of microbiological methods
Environmental organic pollutants, identified as Polycyclic Aromatic Hydrocarbons (PAHs), are widespread and toxic. These hydrocarbons are commonly produced by industrial activities, burning fossil fuels, and crude oil discharges. Their high hydrophob... read more 

Explainable 3D VGG-style convolutional neural network for pediatric hydrocephalus detection on computed tomography: A segmentation-free and fully volumetric deep learning framework.

Neuroscience
Pediatric hydrocephalus is commonly assessed on computed tomography (CT) using manual two-dimensional indices that incompletely reflect the ventricular system. We developed and evaluated an explainable, segmentation-free three-dimensional convolution... read more 

Interpretable three-dimensional deep learning identifies and reveals the spatial Microstructure of multi-enzyme degradation of lignocellulose.

Bioresource technology
Understanding the spatial mechanisms of multi-enzyme lignocellulose deconstruction is hindered by the lack of spatial quantification and nondestructive analytical methods. This study established an interpretable three-dimensional (3D) deep learning f... read more