Artificial Intelligence Medical Compendium

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

Showing 65,911 to 65,920 of 232,257 articles

The CFDE Workbench: Integrating Metadata and Processed Data from Common Fund Programs.

Journal of molecular biology
The NIH Common Fund Data Ecosystem (CFDE) program was established to facilitate data accessibility and interoperability across multiple Common Fund (CF) programs, promote collaborations and accelerate discoveries by combining diverse data types from ... read more 

Diffusion spectrum imaging-based machine learning for temporal lobe epilepsy lateralization.

Brain research
OBJECTIVE: Accurate preoperative lateralization of temporal lobe epilepsy (TLE) remains challenging, particularly in cases with subtle or MRI-negative lesions. This study aimed to overcome limitations of conventional MRI by developing a diffusion spe... read more 

Machine learning reveals sex-biased platelet-associated molecular signatures in systemic lupus erythematosus.

Immunology letters
OBJECTIVES: Autoimmune diseases (ADs) demonstrate a higher prevalence in women than men. Systemic Lupus Erythematosus (SLE) stands out among multiple ADs as an extreme case of the imbalanced sex ratio observed at disease onset, predominantly affectin... read more 

Acute kidney injury: Detection, risk stratification, and predictive biomarkers.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Acute kidney injury (AKI) is a complex multifactorial syndrome characterized by a rapid decline in kidney function, frequently observed in hospitalized and critically ill patients. Despite its high morbidity and mortality, current diagnos... read more 

Depression detection from speech data using deep learning-based optimized temporal-frequency-channel attention with interpretable acoustic-prosodic mapping.

Journal of affective disorders
Detecting depression from voice recordings is challenging because acoustic indicators are often highly subtle and vary broadly among individuals. A key drawback of current models is their poor cross-lingual generalization; they often degrade sharply ... read more 

Advancing patient stratification in major depressive disorder: Evaluation of clinical staging and machine learning prediction models based on real-world data.

Journal of affective disorders
OBJECTIVE: To evaluate the utility of a clinical staging model and compared its prognostic performance with an unsupervised machine learning-based stratification method in a real-world cohort of patients with Major Depressive Disorder (MDD). METHODS:... read more 

Exploring temperamental and clinical predictors of lithium treatment outcomes in bipolar disorder using diverse machine learning approaches.

Journal of affective disorders
BACKGROUND: Lithium is a core treatment for bipolar disorder (BD), yet clinical response varies across patients. Testing accessible predictors of lithium response is critical for personalization strategies in real-world settings. METHODS: In this cro... read more 

Driving mechanisms of vegetation carbon sink distribution based on explainable machine learning and evaluation of carbon sequestration in open-pit mines.

Environmental research
Vegetation carbon sequestration plays a crucial role in mitigating global warming and maintaining regional carbon balance. The Yellow River Basin (YRB) is a key region for energy development and ecological conservation in China, yet the driving mecha... read more 

Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non-small cell lung cancer.

Cancer letters
Tumor-intrinsic biomarkers alone insufficiently predict pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) in non-small cell lung cancer (NSCLC). Artificial intelligence (AI)-based three-dimensional CT-derived body composit... read more