Artificial Intelligence Medical Compendium

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

Showing 3,821 to 3,830 of 203,626 articles

DG-LSTM-SA model: A deep gated LSTM network with self-attention mechanism for power generation and load forecasting.

PloS one
Accurate forecasting of power generation and load demand is essential for the reliable operation of modern energy systems. Traditional recurrent neural networks (RNNs) often struggle to capture long-term dependencies in complex power time series, whe... read more 

Research on anomaly detection and operational status evaluation methods for smart electricity meters based on hybrid deep learning.

PloS one
To address the limitations of single-image feature information and the insufficient recognition capability of traditional power quality disturbance (PQD) identification systems, this paper proposes a PQD recognition method based on feature-image comb... read more 

Reliability assessment of key equipment for coal gasification using artificial intelligence technology.

PloS one
To address the gap in quantitatively modeling dynamic failure mechanisms for Gasifier lock bucket valve system reliability, this study proposes an innovative method: using backpropagation (BP) neural network to optimize the prior data of dynamic Baye... read more 

Radiologist workforce challenges and the burden of image interpretation in Ghana: Perspectives of frontline doctors and implications for healthcare delivery.

PLOS global public health
Interpreting radiological images, a primary responsibility of radiologists, is crucial for accurate diagnosis and informed clinical decisions. However, many low-and-middle-income countries (LMICs) face severe radiologist shortages, leading to diagnos... read more 

Integration of single-cell and bulk RNA sequencing reveals programmed cell death-associated transcriptional programs in sepsis-induced acute lung injury.

PloS one
BACKGROUND: Sepsis-induced acute lung injury (ALI) is a frequent and life-threatening complication of sepsis, yet clinically actionable transcriptomic biomarkers remain limited. Regulated/programmed cell death (PCD) pathways shape inflammatory injury... read more 

A mechatronic and artificial intelligence-driven framework for automated non-invasive knee abnormality screening using multimodal sensor data.

Computer methods in biomechanics and biomedical engineering
Current knee-abnormality detection relies on costly Magnetic Resonance Imaging (MRI) and subjective clinical evaluation, limiting accessibility. This study presents an integrated mechatronic and machine-learning framework using surface electromyograp... read more 

Cost-Effectiveness of AI-Assisted Kellgren-Lawrence Grading of Knee Osteoarthritis in the South Korean Health-Care System.

The Journal of bone and joint surgery. American volume
BACKGROUND: Early diagnosis of knee osteoarthritis (KOA) is often delayed due to reliance on subjective interpretation of radiographs. Recent advances in artificial intelligence (AI)-based automated Kellgren-Lawrence (KL) grading offer the potential ... read more 

Two decades of human- and climate-induced groundwater storage shifts in Brazil.

Science advances
Brazil holds the world's largest reserves of renewable fresh water, yet recurrent water crises expose its growing vulnerability under extreme events. As the nation's groundwater demand increases, these reserves still are poorly monitored. Here, we pr... read more 

Implementation of the EPIC Deterioration Index Tool on a Medical/Surgical Unit.

Clinical nurse specialist CNS
PURPOSE: Early detection is crucial for preventing clinical deterioration. This quality improvement project aimed to investigate the application of a machine-based learning tool in the medical/surgical setting. DESCRIPTION: This quality improvement p... read more 

Development and Interpretability Analysis of a Stacking Ensemble Model for Early Prediction of Nutritional Risk in Intensive Care Unit Patients: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Malnutrition in critically ill patients is associated with increased morbidity and mortality, yet traditional screening tools such as the modified NUTRIC (mNUTRIC) score often rely on subjective assessments or delayed data, limiting their... read more