Artificial Intelligence Medical Compendium

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

Showing 3,311 to 3,320 of 168,679 articles

Machine learningdriven framework for realtime air quality assessment and predictive environmental health risk mapping.

Scientific reports
This research introduces a practical and innovative approach for real-time air quality assessment and health risk prediction, focusing on urban, industrial, suburban, rural, and traffic-heavy environments. The framework integrates data from multiple ... read more 

Adaptive context biasing in transformer-based ASR systems.

Scientific reports
With the advancement of neural networks, end-to-end neural automatic speech recognition (ASR) systems have demonstrated significant improvements in identifying contextually biased words. However, the incorporation of bias layers introduces additional... read more 

Public Medical Appeals and Government Online Responses: Big Data Analysis Based on Chinese Digital Governance Platforms.

Journal of medical Internet research
BACKGROUND: In the era of internet-based governance, online public appeals-particularly those related to health care-have emerged as a crucial channel through which citizens articulate their needs and concerns. read more 

Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network.

Scientific reports
Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with subtle early symptoms leading to delayed diagnosis. Ferroptosis, a cell death process associated with iron metabolism dysregulation, has been linked t... read more 

A Machine Learning-Based Prognostication Model Enhances Prediction of Early Hepatic Encephalopathy in Patients With Noncancer-Related Cirrhosis: Multicenter Longitudinal Cohort Study in Taiwan.

JMIR medical informatics
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ... read more 

Deep learning-based radiomics does not improve residual cancer burden prediction post-chemotherapy in LIMA breast MRI trial.

European radiology
OBJECTIVES: This study aimed to evaluate the potential additional value of deep radiomics for assessing residual cancer burden (RCB) in locally advanced breast cancer, after neoadjuvant chemotherapy (NAC) but before surgery, compared to standard pred... read more 

Decoding Covert Visual Attention in Space and Time from Neural Signals.

Annual review of vision science
Visual attention prioritizes relevant stimuli in complex environments through top-down (goal-directed) and bottom-up (stimulus-driven) mechanisms within cortical networks. This review explores the neural mechanisms underlying visual attention, focusi... read more 

Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.

Scientific reports
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi... read more 

An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments.

Scientific reports
The fast development of Internet of Things (IoT) tools in smart cities has presented many advantages, improving sustainability, automation, and urban efficiency. Still, these interlinked systems further pose critical cybersecurity difficulties, inclu... read more 

Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approaches.

Scientific reports
Brain tumors are a significant challenge to human health as they impair the proper functioning of the brain and the general quality of life, thus requiring clinical intervention through early and accurate diagnosis. Although current state-of-the-art ... read more