AIMC Topic: Humans

Clear Filters Showing 6441 to 6450 of 95995 articles

Data-driven trends in critical care informatics: a bibliometric analysis of global collaborations using the MIMIC database (2004-2024).

Computers in biology and medicine
BACKGROUND: The Medical Information Mart for Intensive Care (MIMIC) database has become a cornerstone resource for critical care research, enabling advances in outcome prediction, machine learning, and patient management. However, comprehensive bibli...

SER inspired deep learning approach to detect cardiac arrhythmias in electrocardiogram signals using Temporal Convolutional Network and graph neural network.

Computers in biology and medicine
Electrocardiogram (ECG) signals play a critical role in diagnosing cardiovascular diseases (CVDs), yet automated ECG classification remains challenging due to inter-patient variability, signal noise, and heart rhythm complexity. To address these chal...

A comprehensive hybrid model: Combining bioinspired optimization and deep learning for Alzheimer's disease identification.

Computers in biology and medicine
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive ability and memory function. It is a progressive disease characterized by worsening dementia symptoms over time, starting with mild m...

Blockchain-aided comparative study of heart disease detection using machine learning-based approaches with an expanded dataset.

Computers in biology and medicine
Heart disease, also known as cardiovascular disease (CVD), is a diverse set of conditions that disrupt the normal functioning of the cardiovascular system by narrowing the coronary arteries. These arteries are used for blood circulation and the deliv...

An interpretable stacking ensemble learning model for visual-manual distraction level classification for in-vehicle interactions.

Accident; analysis and prevention
Recognizing the level of driver distraction during the execution of secondary tasks within the intelligent cockpit is crucial for ensuring a seamless interaction between human drivers and intelligent vehicle systems. To address this issue, this paper...

Harnessing generative neural networks to fuse traditional Tujia Baishou dance with contemporary choreography: Enhancing creativity and aesthetic experience in dance students.

Acta psychologica
The objective of this study was to explore the potential of using the generative neural network Dance2Dance to integrate elements of the traditional Tujia Baishou dance with modern choreography, specifically examining the impact of such technologies ...

Aortic Stenosis and Mitral Regurgitation: Takeaways From the Heart Valve Collaboratory Workshop on Multivalvular Disease.

Journal of the American College of Cardiology
The management of multivalvular disease presents increasing challenges in clinical practice caused by complex hemodynamic interactions and limited guideline-based recommendations. As part of the inaugural collaboration between JACC and the Heart Valv...

Technology Roadmap of Micro/Nanorobots.

ACS nano
Inspired by Richard Feynman's 1959 lecture and the 1966 film , the field of micro/nanorobots has evolved from science fiction to reality, with significant advancements in biomedical and environmental applications. Despite the rapid progress, the depl...

Discovery of SARS-CoV-2 papain-like protease inhibitors through machine learning and molecular simulation approaches.

Drug discoveries & therapeutics
The papain-like protease (PLpro), a cysteine protease found in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), plays a crucial role in viral replication by cleaving the viral polyproteins and interfering with the host's innate immune re...

A Feasibility Study of a Video-Based Application by Parents of Infants Born Full-Term and Preterm.

Pediatric physical therapy : the official publication of the Section on Pediatrics of the American Physical Therapy Association
PURPOSE: To examine the factors that influence the usability of a video-based mobile application (app) by parents of infants born full-term and preterm.