AIMC Topic:
Middle Aged

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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Scientific reports Feb 8, 2025
Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major cause of death. We analyzed longitudinal data with a median 19-month follow-up. BC was diagnosed with ultrasounds and MRCP. Missing data was imputed u...
Middle Aged Postoperative Complications Biliary Tract Diseases Liver Transplantation Risk Factors Aged Adult Survival Rate Male Humans Machine Learning Female
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Advancing Alzheimer's disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study.

BMJ open Feb 8, 2025
OBJECTIVES: Alzheimer's disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate high accuracy, their complexity and limited access...
Risk Assessment Logistic Models Alzheimer Disease Humans Machine Learning Female Risk Factors Cross-Sectional Studies Male Middle Aged Aged Aged, 80 and over
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Analyzing patterns of frequent mental distress in Alzheimer's patients: A generative AI approach.

Journal of the National Medical Association Feb 8, 2025
This study tackles creating Python code for beginners with generative AI and analyzing trends in mental distress among Alzheimer's patients in the US (2015-2022 CDC data). It guides beginners through using AI to generate code for visualizing these tr...
Alzheimer Disease Artificial Intelligence Sex Factors Female Aged Middle Aged Humans Aged, 80 and over Stress, Psychological Male United States Age Factors
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Developing approaches to incorporate donor-lung computed tomography images into machine learning models to predict severe primary graft dysfunction after lung transplantation.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons Feb 7, 2025
Primary graft dysfunction (PGD) is a common complication after lung transplantation associated with poor outcomes. Although risk factors have been identified, the complex interactions between clinical variables affecting PGD risk are not well underst...
Humans Middle Aged Tissue Donors Graft Survival Follow-Up Studies Female Machine Learning Risk Factors Lung Transplantation Prognosis Adult Primary Graft Dysfunction Retrospective Studies Male Tomography, X-Ray Computed
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Characterizing drivers of change in intraoperative cerebral saturation using supervised machine learning.

Journal of clinical monitoring and computing Feb 7, 2025
Regional cerebral oxygen saturation (rSO) is used to monitor cerebral perfusion with emerging evidence that optimization of rSO may improve neurological and non-neurological outcomes. To manipulate rSO an understanding of the variables that drive its...
Adult Supervised Machine Learning Male Monitoring, Intraoperative Carbon Dioxide Brain Humans Middle Aged ROC Curve Female Machine Learning Spectroscopy, Near-Infrared Oxygen Reproducibility of Results Hemodynamics Oxygen Saturation Signal Processing, Computer-Assisted Aged Cerebrovascular Circulation Oximetry Algorithms
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Artificial Intelligence Job Substitution Risks, Digital Self-efficacy, and Mental Health Among Employees.

Journal of occupational and environmental medicine Feb 7, 2025
OBJECTIVE: Artificial intelligence (AI) becomes increasingly integrated into the workplace, its associated job substitution risks for employees are more evident, resulting in significant repercussions for their well-being. This study tries to elucida...
Self Efficacy Mental Health Humans Workplace Male Artificial Intelligence Employment Middle Aged Female Surveys and Questionnaires Adult
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A Hybrid Machine Learning CT-Based Radiomics Nomogram for Predicting Cancer-Specific Survival in Curatively Resected Colorectal Cancer.

Academic radiology Feb 7, 2025
RATIONALE AND OBJECTIVES: To develop and validate a computed tomography-based radiomics nomogram for cancer-specific survival (CSS) prediction in curatively resected colorectal cancer (CRC), and its performance was compared with the American Joint Co...
Male Middle Aged Nomograms Neoplasm Staging Female Aged Colorectal Neoplasms Radiomics Prospective Studies Prognosis Tomography, X-Ray Computed Humans Machine Learning
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Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction.

Drug safety Feb 7, 2025
BACKGROUND: Safety signals for potential drug-induced adverse events (AEs) typically emerge from multiple data sources, primarily spontaneous reporting systems, despite known limitations. Increasingly, real-world data from sources such as electronic ...
Machine Learning Databases, Factual Electronic Health Records Female Aged Humans Drug-Related Side Effects and Adverse Reactions Cross-Over Studies Proof of Concept Study Adverse Drug Reaction Reporting Systems Male Middle Aged Italy Myocardial Infarction
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Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

European journal of radiology Feb 7, 2025
PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...
Male Middle Aged Deep Learning Humans Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Female Aged, 80 and over Retrospective Studies Kidney Neoplasms Adult Reproducibility of Results Tomography, X-Ray Computed Carcinoma, Renal Cell Sensitivity and Specificity Aged Radiomics
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Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

JMIR medical informatics Feb 7, 2025
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...
Aged Young Adult Adult Male Renal Insufficiency, Chronic Glomerular Filtration Rate Retina Middle Aged Deep Learning Humans Female Urinalysis
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