AIMC Topic: Machine Learning
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Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.
Journal of health, population, and nutrition
Jun 4, 2025
BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM i...
Machine learning in dentistry and oral surgery: charting the course with bibliometric insights.
Head & face medicine
Jun 4, 2025
BACKGROUND: We aimed to comprehensively analyze the application of machine learning (ML) in dentistry and oral surgery using bibliometric methods to identify research trends, hotspots, and future directions.
HLN-DDI: hierarchical molecular representation learning with co-attention mechanism for drug-drug interaction prediction.
BMC bioinformatics
Jun 4, 2025
BACKGROUND: Accurate identification of drug-drug interactions (DDIs) is critical in pharmacology, as DDIs can either enhance therapeutic efficacy or trigger adverse reactions when multiple medications are administered concurrently. Traditional method...
Machine learning-based prediction of respiratory depression during sedation for liposuction.
Scientific reports
Jun 4, 2025
Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early detection of respiratory compromise could not only enhance patient safety during procedural sedation...
UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.
World journal of urology
Jun 4, 2025
PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting beni...
Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.
Scientific reports
Jun 4, 2025
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...
Identification of key proteins and pathways in myocardial infarction using machine learning approaches.
Scientific reports
Jun 4, 2025
Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning...
Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.
Scientific reports
Jun 4, 2025
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...
Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.
Scientific reports
Jun 4, 2025
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...
Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models.
Scientific reports
Jun 4, 2025
For analysis of crystallization, the solubility of drug in solvents should be correlated to input parameters. In this investigation, the solubility of salicylic acid as drug model in a variety of solvents is predicted through the utilization of multi...
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