Anemia

CT-based Intratumoral Heterogeneity Score for Preoperative Prediction of Lymphovascular Invasion and Prognosis in Lung Adenocarcinoma: A Multicenter Validation and Radiogenomic Interpretation.

BACKGROUND: Lymphovascular invasion (LVI) is a key determinant of recurrence and survival in lung adenocarcinoma (LUAD), but preoperative identification remains challenging. We developed and validated a CT-based intratumoral heterogeneity (ITH) score for LVI prediction, prognostic stratification, and exploratory radiogenomic interpretation. METHODS: We retrospectively included 1322 patients from t...

Acoustic emission-based intelligent identification and dual early warning for coal fatigue failure under multistage cyclic loading.

To address the limitations of insufficient accuracy and timeliness in the early warning of coal instability under multistage cyclic loading, this paper proposes an intelligent recognition and dual early warning method for coal damage based on acoustic emission parameters. The multistage cyclic compression test of coal is performed to obtain five acoustic emission parameters, and the average event ...

Harnessing AI and social media to understand real-world patient experiences in SLE.

OBJECTIVE: To apply large language models (LLMs) to Reddit posts referencing SLE to identify patient-expressed unmet medical needs, symptom experience...

Deep behavioral phenotyping reveals novel features in a mouse model of metabolic dysfunction-associated steatohepatitis.

Patients with metabolic dysfunction-associated steatohepatitis (MASH) often suffer from a broad range of extrahepatic symptoms including fatigue and p...

Sex-specific predictors of lower-limb strength: an interpretable machine learning analysis of anthropometric and body composition measures.

Muscular strength is a key indicator of physical function. However, its direct laboratory assessment often requires specialized, high-cost equipment a...

Multiomics integrative bioinformatics analysis of gene expression characteristics and molecular mechanisms in preeclampsia placental tissue.

Preeclampsia (PE) is a severe pregnancy-specific complication characterized by new-onset hypertension and proteinuria after 20 weeks of gestation, whi...

Early Prediction of Critical Care Interventions From Pediatric Emergency Department Triage.

BACKGROUND AND OBJECTIVES: Most pediatric emergency departments (EDs) in the United States use Emergency Severity Index (ESI) system to triage patient...

Dual-stream feature fusion network for landslide detection.

Landslides are destructive natural hazards that threaten infrastructure, ecosystems, and human settlements, particularly in mountainous regions. Altho...

SMFF-Net: Spatiotemporal-frequency Multi-domain Feature Fusion Network for EEG-based brain state detection.

The timely and reliable detection of driver fatigue is crucial for reducing driving risks and improving traffic safety. EEG-based deep learning approa...

Hypoxia tumor-associated macrophages facilitate hepatocellular carcinoma metastasis via uPA-uPAR pathway.

BACKGROUND: Hepatocellular carcinoma (HCC) arises within a hypoxic and immunosuppressive tumor microenvironment (TME), where tumor-associated macropha...

Bias and Fairness Across the Healthcare AI Lifecycle: A Clinician-Oriented Review.

Artificial intelligence (AI) is increasingly being investigated and, in selected clinical settings, implemented to support diagnosis, triage, and work...

Deep learning reveals FLAD1-mediated mitochondrial metabolic reprogramming in hypoxic tumors.

Hypoxia, a hallmark of solid tumors, drives malignant progression and represents a major therapeutic challenge. Metabolic reprogramming induced by hyp...

System for activity-aware fatigue evaluation (SAFE) framework: Predictive fatigue modelling for occupational tasks.

The SAFE (System for Activity-aware Fatigue Evaluation) framework integrates wearable sensing, biomechanical modelling, and task detection to enable m...

DETERIO-LLM: enhancing traditional deterioration risk scores with clinical context and advanced reasoning.

OBJECTIVES: Accurate and timely prediction of physiological deterioration in hospitalized patients is essential, but existing deep learning models, wh...

Natural language processing identifies symptoms predicting complete coronary artery occlusion in patients with NSTEMI.

AIMS: One in 10 patients present to the emergency department (ED) with symptoms of acute coronary syndrome (ACS). The 13-item ACS Symptom Checklist is...

Biomarkers in predicting mortality in hemodialysis patients: recent advances.

Patients undergoing maintenance hemodialysis face annual mortality rates of 15-27%, with cardiovascular causes accounting for more than half of all de...

Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.

Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result in significant morbidity, most notably with ocula...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...

Wearable fatigue detection system for wheelchair propulsion: Identifying key muscles via an attention-based LSTM Model.

Fatigue induces adverse short- and long-term health risks in wheelchair users. This study aimed to develop a machine learning approach to predict fati...

Personalized survival prediction in elderly dialysis patients: integrating machine learning with traditional survival analysis.

BACKGROUND: Elderly patients undergoing kidney replacement therapy (KRT) face high mortality rates. Traditional statistical models describe overall su...