Artificial Intelligence Medical Compendium

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

Showing 4,981 to 4,990 of 174,202 articles

Convolutional autoencoder network lithology recognition based on scratch tests.

Scientific reports Aug 19, 2025
To address the characteristic of frequent lithological alternations in the continental shale of the Songliao Basin in China and meet the refined requirements of reservoir modeling, it is necessary to establish a higher-precision lithology identificat... read more 

Understanding the Impact of AI Doctors' Information Quality on Patients' Intentions to Adopt AI for Independent Diagnosis: Scenario-Based Experimental Study.

Journal of medical Internet research Aug 19, 2025
BACKGROUND: The development of artificial intelligence (AI) systems capable of independent diagnosis offers a promising solution for optimizing medical resource allocation, especially as their diagnostic accuracy can exceed that of some primary medic... read more 

Graph neural network-based drug-drug interaction prediction.

Scientific reports Aug 19, 2025
With the growing variety of pharmacological compounds and the increasing need for polypharmacy, accurately predicting drug-drug interactions (DDIs) is essential to ensure both treatment efficacy and patient safety. Beneficial DDIs can enhance therape... read more 
Humans Neural Networks, Computer Algorithms Drug Interactions Graph Neural Networks

Exploring the Application of AI and Extended Reality Technologies in Metaverse-Driven Mental Health Solutions: Scoping Review.

Journal of medical Internet research Aug 19, 2025
BACKGROUND: Mental health systems worldwide face unprecedented strain due to rising psychological distress, limited access to care, and an insufficient number of trained professionals. Even in high-income countries, the ratio of patients to health ca... read more 

Emerging modalities for neuroprognostication in neonatal encephalopathy: harnessing the potential of artificial intelligence.

Pediatric research Aug 19, 2025
Neonatal Encephalopathy (NE) from presumed hypoxic-ischemic encephalopathy (pHIE) is a leading cause of morbidity and mortality in infants worldwide. Recent advancements in HIE research have introduced promising tools for improved screening of high-r... read more 

CT-based auto-segmentation of multiple target volumes for all-in-one radiotherapy in rectal cancer patients.

Radiation oncology (London, England) Aug 19, 2025
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Real-world data of CanAssist Breast- first immunohistochemistry and AI-based prognostic test.

Scientific reports Aug 19, 2025
CanAssist Breast (CAB), an immunohistochemistry (IHC) and artificial intelligence-based prognostic test, was developed on Hormone receptor-positive (HR +), HER2/neu-negative (HER2-) breast tumors from Indian patients and validated in retrospective gl... read more 
Humans Artificial Intelligence Prognosis Retrospective Studies Female Aged Adult Breast Neoplasms Biomarkers, Tumor Middle Aged Neoplasm Recurrence, Local Immunohistochemistry Receptor, ErbB-2 Receptors, Progesterone

Comparative performance of deep learning architectures for diabetic peripheral neuropathy detection using corneal confocal microscopy: a retrospective single-centre study.

BMJ open Aug 19, 2025
OBJECTIVES: This study aims to develop a deep learning algorithm (DLA) using the InceptionV3 architecture for effective diabetic peripheral neuropathy (DPN) screening via corneal confocal microscopy (CCM) images. read more 
Humans Algorithms Retrospective Studies Female Aged Adult Cornea Male Middle Aged Deep Learning Microscopy, Confocal Diabetic Neuropathies

A plasma proteomics-based candidate biomarker panel predictive of amyotrophic lateral sclerosis.

Nature medicine Aug 19, 2025
Identifying a reliable biomarker for amyotrophic lateral sclerosis (ALS) is crucial for clinical practice. Here, in this cross-sectional study, we used the Olink Explore 3072 platform to investigate plasma proteomics as a biomarker tool for this neur... read more 

The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning.

Nature communications Aug 19, 2025
Many genome-wide studies capture isolated moments in cell differentiation or organismal development. Conversely, longitudinal studies provide a more direct way to study these kinetic processes. Here, we present an approach for modeling gene-expressio... read more 
Neural Networks, Computer Machine Learning Brain Animals Single-Cell Analysis Mice Multiomics Models, Genetic Kinetics Chromatin
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