Artificial Intelligence Medical Compendium

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

Showing 2,751 to 2,760 of 167,235 articles

Beyond RGB and Events: Enhancing Object Detection under Adverse Lighting with Monocular Normal Maps

arXiv
Accurate object detection under adverse lighting conditions is critical for real-world applications such as autonomous driving. Although neuromorphic event cameras have been introduced to handle these scenarios, adverse lighting often induces distr... read more 

Evaluating microstructural and machine learning predictive models for friction drilling of sustainable snail shell reinforced aluminium matrix composites.

Scientific reports
For lightweight automotive applications, friction drilling is a choice candidate for ecofriendly drilling of aluminium matrix composites (AMCs) with green snail shell reinforcement. The present work investigates the effects of significant process var... read more 

FIBOS: R and python packages for analyzing protein packing and structure.

Bioinformatics (Oxford, England)
MOTIVATION: Advances in prediction of the 3D structures of most known proteins through machine learning have achieved unprecedented accuracies. However, although these computed models are remarkably good, they still challenge accuracy at the atomic l... read more 

Gene expression cluster differences and molecular correlation with the STING pathway in orbital MALT lymphoma and orbital IgG4-related eye disease.

Discover oncology
PURPOSE: Mucosa-associated lymphoid tissue (MALT) lymphoma in the orbital region and IgG4-related ophthalmic disease (IgG4-ROD) account for the majority of mass lesions in the orbital region. These diseases may show similar shadows on radiologic imag... read more 

Artificial intelligence-based digital pathology using H&E-stained whole slide images in immuno-oncology: from immune biomarker detection to immunotherapy response prediction.

Journal for immunotherapy of cancer
Immuno-oncology and the advent of immunotherapies, in particular immune checkpoint inhibitors (ICIs), have fundamentally altered the way we treat cancer. Yet only a small subset of patients actually responds to ICIs, and many face significant adverse... read more 

SplatSSC: Decoupled Depth-Guided Gaussian Splatting for Semantic Scene Completion

arXiv
Monocular 3D Semantic Scene Completion (SSC) is a challenging yet promising task that aims to infer dense geometric and semantic descriptions of a scene from a single image. While recent object-centric paradigms significantly improve efficiency by ... read more 

Synergistic Scale for AI Integration in Spiritual Leadership and Educational Management Transformation (Ssai-Slem): Development, Network Analysis, and Validation Among Jordanian Secondary School Administrators.

Journal of religion and health
The purpose of this study was twofold: first, to develop a new 36-item SSAI-SLEM scale for measuring synergy in integrating AI into spiritual leadership and educational management transformation; and second, to examine its psychometric properties. Th... read more 

GPU in the Blind Spot: Overlooked Security Risks in Transportation

arXiv
Graphics processing units (GPUs) are becoming an essential part of the intelligent transportation system (ITS) for enabling video-based and artificial intelligence (AI) based applications. GPUs provide high-throughput and energy-efficient computing... read more 

From Photons to Physics: Autonomous Indoor Drones and the Future of Objective Property Assessment

arXiv
The convergence of autonomous indoor drones with physics-aware sensing technologies promises to transform property assessment from subjective visual inspection to objective, quantitative measurement. This comprehensive review examines the technical... read more 

Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b... read more