CT radiomics model predicts poor chemotherapy response in esophageal cancer before treatment
A dual-center study found that a CT-based radiomics model using four texture features predicted poor pathological response to neoadjuvant chemotherapy ...
Tag: Machine Learning
EEG Deep Learning Framework Classifies Parkinson’s Disease with Interpretable Analysis
A new attention-based deep learning framework classifies Parkinson’s disease from resting-state EEG signals with high accuracy and provides interpretable sub-band ...
Tongue Images May Offer Early Warning of NEC
Researchers propose a non-invasive framework using tongue image analysis to detect early signs of necrotizing enterocolitis in neonates.
AI in Dentistry: Review Maps Current Uses and Future Challenges
A narrative review in BMC Artificial Intelligence examines the current applications and future challenges of AI in dental practice, highlighting ...
Global Collaborative Learning Framework Resolves Core Conflicts in Modern Object Detection
Researchers introduce Global Collaborative Learning to align object localization and classification by mining sub-hard training samples and enabling cross-task feature ...
SMARTHEP Network Trains PhD Students in Real-time Physics Analysis
The SMARTHEP Innovative Training Network trained 12 PhD students in machine learning and real-time analysis, bridging high-energy physics and industrial ...
Hybrid Artificial Intelligence Framework Evaluates Higher Education Teaching Effectiveness and Reduces Bias
A hybrid computational framework combining deep learning, fuzzy logic, and metaheuristic optimization achieved superior accuracy and fairness in assessing university ...
Machine Learning Predicts Diabetes Risk in NAFLD Patients
A new machine learning framework using routine clinical variables predicts medium-term type 2 diabetes risk in patients with histologically confirmed ...
Study Benchmarks Eight Antibody Language Models for Design Tasks
A new study in Genome Biology benchmarks eight antibody language models across five design tasks, finding that AbLang, AntiBERTa2, and ...
Temporal Features Boost HVAC Load Forecasting Accuracy
A study in Energy Informatics shows that incorporating temporal load-history information significantly improves the accuracy of short-term HVAC load forecasting ...
PTSS Key Predictor of Self-Harm in Traumatized Teens
A cross-sectional study of 448 Iranian adolescents identifies posttraumatic stress symptoms as the primary predictor of non-suicidal self-injury, with machine ...
Machine Learning Framework Advances Urban Heat Island Mapping and Climate Resilience
Researchers propose an artificial intelligence framework combining satellite imagery and machine learning to map urban heat islands and guide sustainable ...
Machine Learning and Behavioral Models Converge to Reshape Urban Travel Forecasting
A systematic review of 133 studies published from 1998 to 2026 examines how urban travel mode choice modelling evolved from ...
Stereo Cameras Estimate In-Water Fish Weight in Real Time Without Full Depth Maps
Researchers have developed a computer-vision system that estimates the dimensions and weight of free-swimming tilapia in real time without generating ...
Random Forest Model Accurately Predicts Winter PM2.5 Across Riyadh
A machine learning framework combining satellite and reanalysis data accurately predicted winter fine particulate matter levels across Riyadh.
Plasma Metabolites May Predict Individual Treatment Responses in Psoriatic Arthritis
An exploratory analysis of baseline plasma metabolomics in eighty patients with psoriatic arthritis identified candidate biomarkers associated with individual treatment ...
Ten-Factor Risk Score Predicts Cardiovascular Complications in Moderate Aortic Stenosis Patients
A retrospective cohort study developed and externally validated a ten-variable risk score integrating clinical and echocardiographic parameters to predict five-year ...
Systematic Review Evaluates Explainable AI and RDoC Framework in Alzheimer’s Diagnosis
A systematic review of 56 studies demonstrates how combining explainable artificial intelligence with the Research Domain Criteria framework can map ...
Stacked machine learning model predicts concrete strength with high accuracy
A hybrid stacking ensemble of XGBoost, LightGBM and CatBoost with domain-informed features predicts concrete compressive strength with an R² of ...
Review Details AI, Robotics, and Language Models in Remote Patient Monitoring
A scientific review published in BMC Artificial Intelligence evaluates how artificial intelligence, robotics, and natural language processing advance telemedicine and ...
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