Artificial Intelligence Medical Compendium

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

Showing 18,921 to 18,930 of 214,544 articles

ChatGPT as a tool for reviewing multiple-choice questions in the health sector.

Scientific reports May 13, 2026
Artificial Intelligence (AI), particularly ChatGPT-4, offers promising applications in medical education, including multiple-choice question (MCQ) development. This study aimed to evaluate and compare the quality of 36 MCQs created by medical faculty... read more 

Faculty perceptions of AI for personalized instruction and learning facilitation in higher education.

Scientific reports May 13, 2026
This study examines university faculty members' perceptions of how artificial intelligence (AI) supports personalized instruction and facilitates learning opportunities in higher education. Given the exploratory nature of AI-based pedagogical practic... read more 

MultiDentNet: a unified deep learning framework for multi-class dental condition screening and preliminary oral lesion triage.

Scientific reports May 13, 2026
To develop and evaluate MultiDentNet, a unified deep learning framework for multi-class dental condition screening and preliminary risk stratification of cancer-suspicious oral lesions, utilizing backbone-diverse ensembling and inter-class relational... read more 

Integrating fuzzy logic and neural networks with multi-criteria decision-making for intelligent evaluation of drug compound design attributes.

Scientific reports May 13, 2026
This study proposes a fuzzy machine learning framework for optimizing antiepileptic drug selection using Quantitative Structure-Property Relationship (QSPR) modeling under pharmacological uncertainty. Feature relevance was assessed using Random Fores... read more 

Element-to-mineral-properties conversion (EMPC) via MARSpline for 3D geometallurgical modeling of the Koashva Apatite-Nepheline Deposit, Kola Peninsula, Russia.

Scientific reports May 13, 2026
Efficient processing of complex ores is often hampered by an incomplete understanding of the spatial distribution of critical mineralogical properties. Here, we introduce a machine learning-based framework that addresses this gap. Using the multivari... read more 

Optimizing material and process parameters in laser engineered net shaping using liquid neural networks.

Scientific reports May 13, 2026
This study introduces a physics-based Liquid Neural Network (LNN) framework for optimization of material and process parameters in Laser Engineered Net Shaping (LENS). The model combines neural differential equations with dynamic liquid weight mechan... read more 

An intelligent IoT-machine learning framework for wildfire detection and prediction using a hybrid RF-XGB model.

Scientific reports May 13, 2026
Forest fires in Turkey have received comparatively limited scholarly attention despite the country's high seasonal susceptibility, particularly during summer due to adverse climatic conditions. For real-time detection and risk assessment, this resear... read more 

An evaluation of various parts of face to identify facial paralysis using temporal convolutional neural network model.

Scientific reports May 13, 2026
Facial paralysis severely changes the individual's life and enlarges the physician's need for precise analysis and grading of facial paralysis for appropriate rehabilitation and treatment. A patient with facial paralysis will have asymmetry of their ... read more 

UveAI: clinic-ready scoring of retinal inflammation in uveitis on widefield fluorescein angiography using AI.

Scientific reports May 13, 2026
Retinal inflammation is a key determinant of visual prognosis in uveitis, yet its assessment on fluorescein angiography remains subjective, labor-intensive, and insufficiently scalable for clinical trials or large cohort studies. Fluorescein angiogra... read more 

Hessian-guided mixed-precision quantization of vision transformers under hardware constraints.

Scientific reports May 13, 2026
Vision transformers (ViTs) have attracted increasing attention in visual tasks due to their strong global modeling capability. However, compared with conventional convolutional neural networks, ViTs typically involve substantially more parameters and... read more 
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