Artificial Intelligence Medical Compendium

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

Showing 1 to 10 of 210,436 articles

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Jul 13, 2026
OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spinal triangle concept is proposed, integrating a digital model to establish standardized reference parameters and technical protocols for biportal positi... read more 

A Radiomics-Driven Model to Distinguish Between Clinically Similar Myxopapillary Ependymomas and Lumbosacral Schwannomas.

Neurosurgery practice Jul 13, 2026
BACKGROUND AND OBJECTIVES: Myxopapillary ependymomas (MPE) and intradural lumbosacral schwannomas may be challenging to distinguish based on presenting characteristics and preoperative imaging. Accurate differentiation is crucial, as MPEs carry a ris... read more 

Nr1d1 Mediates Microglial Inflammatory Activation Induced by Intermittent Hypoxia: A Transcriptomic and Machine Learning Study.

Journal of molecular neuroscience : MN Jul 11, 2026
Obstructive sleep apnea is characterized by recurrent intermittent hypoxia (IH), which contributes to neuroinflammation and neurological dysfunction. Microglia are pivotal regulators of inflammatory responses in the central nervous system, but the mo... read more 

The role of health literacy and attitudes toward artificial intelligence in the acceptance of telemedicine services among adults in Turkey: a cross-sectional study.

BMC primary care Jul 13, 2026
BACKGROUND: The digital transformation in healthcare has led to an increase in the use of telemedicine and artificial intelligence (AI)based applications. This study aims to examine the associations between e-health literacy, attitudes toward AI, and... read more 

An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.

Infectious diseases of poverty Jul 13, 2026
BACKGROUND: Worldwide, anemia in children under-five is a major public health issue, particularly in sub-Saharan Africa. Sub-Saharan Africa also has the highest burden of malaria. This study aimed to develop an ensemble machine learning model to esti... read more 

SERS-based spectral analysis of ITS1 PCR products for differentiation of three old world Leishmania species.

Lasers in medical science Jul 13, 2026
Leishmaniasis, a zoonotic disease caused by parasites of the genus Leishmania, poses a significant medical and veterinary importance worldwide. This study was designed to explore the potential of SERS-based plasmonic substrate combined with advanced ... read more 

The role of health literacy and attitudes toward artificial intelligence in the acceptance of telemedicine services among adults in Turkey: a cross-sectional study.

BMC primary care Jul 13, 2026
BACKGROUND: The digital transformation in healthcare has led to an increase in the use of telemedicine and artificial intelligence (AI)based applications. This study aims to examine the associations between e-health literacy, attitudes toward AI, and... read more 

Bloom's taxonomy-based comparison of artificial intelligence and dental students in restorative dentistry.

BMC medical education Jul 13, 2026
BACKGROUND: The aim of this study is to compare the performance of three large language models (ChatGPT 5, Microsoft Copilot, and Google Gemini 3), with that of dental students using their responses to multiple-choice questions (MCQs) in restorative ... read more 

Performance evaluation of SFP models using ML/DL and feature selection via cost evaluation framework.

Scientific reports Jul 13, 2026
The increasing complexity of software systems (SW) makes fault prevention challenging. Although significant amount of research has explored Software Fault Prediction (SFP). However the extensive comparative analysis of Deep Learning (DL), state-of-th... read more 

Prediction of Exercise Intolerance in the Recovery Period After Cardiovascular Surgery Using Perioperative Clinical Parameters.

Archives of physical medicine and rehabilitation Jul 12, 2026
OBJECTIVE: To develop and validate a machine learning model for predicting reduced exercise capacity at 3 months postoperatively using clinical parameters available at hospital discharge in patients undergoing cardiovascular surgery, as prediction of... read more 
Popular Topics
Recent Journals