Artificial Intelligence Medical Compendium

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

Showing 11,521 to 11,530 of 209,934 articles

Development of a model for design radiation shielding composite aprons using machine learning.

Scientific reports May 25, 2026
This study presents the development and evaluation of a novel lead-free composite for radiation shielding, designed using an artificial neural network (ANN). The ANN model achieved a high predictive accuracy for the mass attenuation coefficient, with... read more 

AI based prediction of post prostatectomy urinary incontinence and its impact on quality of life: development and validation study.

Scientific reports May 25, 2026
Urinary incontinence can affect up to 53% of patients after radical prostatectomy, yet prediction tools rely on binary outcomes, missing heterogeneous recovery patterns. We developed machine-learning models that for the first time predict incontinenc... read more 

Spatio-temporal multi-fault and severity aware diagnosis in WSN via GNN transformers.

Scientific reports May 25, 2026
Wireless Sensor Networks (WSNs) play a perilous role in the IoT environment and other applications, where reliable sensing and timely fault diagnosis are essential for system stability. However, fault behavior in WSNs is inherently complex because of... read more 

Development and external validation of a machine learning-based Cox model for predicting in-hospital survival in classic heatstroke: a multicenter retrospective study.

Scientific reports May 25, 2026
Classical heatstroke (CHS) is a life-threatening condition necessitating accurate prognostic tools for risk stratification. The potential of machine learning to predict clinical outcomes in CHS remains largely unexplored. Our objective was to develop... read more 

FDA_YOLOv8: refined small object detection in unmanned aerial vehicle imagery.

Scientific reports May 25, 2026
Small object detection (SOD) is essential for security monitoring in unmanned aerial vehicle (UAV) imagery. However, the inherently low effective resolution, weak semantic representation, and cluttered background of small objects pose significant cha... read more 

Machine learning driven reservoir property modeling of the AEB-3E reservoir in the Berenice field Egypt.

Scientific reports May 25, 2026
Accurate reservoir characterization in structurally complex fields is essential for optimizing hydrocarbon exploration and production. This study presents a detailed analysis of the AEB-3E reservoir within the Berenice Oil Field. It integrates well l... read more 

A hybrid Granger TCN framework for generating climate analogues and determining the future of agricultural practices.

Scientific reports May 25, 2026
The accurate forecasting of weather parameter facilitates effective analysis of crop yield, and ensures the sustainable allocation of crop usage in domestic purpose. Also, the climate change and human activities have increased the complexity of weath... read more 

UAV-based tree species classification using DenseNet121 with transfer learning on visible light images.

Scientific reports May 25, 2026
This study introduces a cutting-edge approach to tree species classification in environmental monitoring by leveraging UAV-based visible light imagery. Focusing exclusively on visible light images captured by unmanned aerial vehicles (UAVs), we addre... read more 

Machine learning-based optimization of dual subthalamic nucleus and substantia nigra targeting in deep brain stimulation.

NPJ Parkinson's disease May 25, 2026
Advances in deep brain stimulation lead technology have created new opportunities for multi-site network modulation, including applications for freezing of gait, but systematic strategies for trajectory planning are lacking. We evaluated trajectories... read more 

Uncovering subgroup heterogeneity in dyslexia intervention outcomes using explainable machine learning.

NPJ science of learning May 25, 2026
Identifying heterogeneity within literacy intervention outcomes can inform more targeted strategies for dyslexia remediation. Based on prior work that used machine learning to predict literacy intervention responders and non-responders at baseline, t... read more 
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