Artificial Intelligence Medical Compendium

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

Showing 2,831 to 2,840 of 168,134 articles

Chronological age estimation from human microbiomes with transformer-based Robust Principal Component Analysis.

Communications biology
Deep learning for microbiome analysis has shown potential for understanding microbial communities and human phenotypes. Here, we propose an approach, Transformer-based Robust Principal Component Analysis(TRPCA), which leverages the strengths of trans... read more 

ATLASS: An AnaTomicaLly-Aware Self-Supervised Learning Framework for Generalizable Retinal Disease Detection.

IEEE journal of biomedical and health informatics
Medical imaging, particularly retinal fundus photography, plays a crucial role in early disease detection and treatment for various ocular disorders. However, the development of robust diagnostic systems using deep learning remains constrained by the... read more 

Altered gray matter morphometry in psychogenic erectile dysfunction patients: A Surface-based morphometry study.

Scientific reports
Psychogenic erectile dysfunction (pED) is a prevalent male sexual dysfunction lacking organic etiology. Endeavors have been made in previous studies to disclose the brain pathological mechanisms of pED. However, the cortical morphological characteris... read more 

Optimization of sliding control parameters for a 3-dof robot arm using genetic algorithm (GA)

arXiv
This paper presents a method for optimizing the sliding mode control (SMC) parameter for a robot manipulator applying a genetic algorithm (GA). The objective of the SMC is to achieve precise and consistent tracking of the trajectory of the robot ma... read more 

Enhancing Postural Monitoring in Wheelchair Users through Context Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Globally, the number of wheelchair users is steadily increasing. These people often adopt sitting patterns that reflect their functional status. Monitoring the user's postural status can help users and healthcare professionals to treat them. However,... read more 

Machine learning training data: over 500,000 images of butterflies and moths (Lepidoptera) with species labels.

Scientific data
Deep learning models can accelerate the processing of image-based biodiversity data and provide educational value by giving direct feedback to citizen scientists. However, the training of such models requires large amounts of labelled data and not al... read more 

Deep neural network models of emotion understanding.

Cognition & emotion
Deep neural networks (DNNs) provide a useful computational framework for constructing cognitive models of emotion understanding. This paper provides a focused discussion of the use of DNNs in this context. It begins by defining three key components o... read more 

Predictive Modeling of Osteonecrosis of the Femoral Head Progression Using MobileNetV3_Large and Long Short-Term Memory Network: Novel Approach.

JMIR medical informatics
BACKGROUND: The assessment of osteonecrosis of the femoral head (ONFH) often presents challenges in accuracy and efficiency. Traditional methods rely on imaging studies and clinical judgment, prompting the need for advanced approaches. This study aim... read more 

BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images.

NPJ digital medicine
We developed a rapid scanning optical microscope, termed "BlurryScope", that leverages continuous image acquisition and deep learning to provide a cost-effective and compact solution for automated inspection and analysis of tissue sections. This devi... read more 

Modeling highway-rail grade crossing (HRGC) crash severity using statistical and machine learning methods.

International journal of injury control and safety promotion
A principal safety issue at highway-rail grade crossings (HRGCs) is the severity of crashes. Although many studies have analyzed crash severity at HRGCs, they often rely on national datasets or a narrow set of variables, frequently overlooking region... read more