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Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.
Computers in biology and medicine
Mar 23, 2025
To prevent chronic disease from getting worse, it is important to detect and predict it at an early stage. Therefore, the accuracy of the prediction is particularly important. To investigate the accuracy of different methods, this study compares the ...
New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort.
European journal of clinical investigation
Mar 22, 2025
BACKGROUND: The validation of a combination of plasma biomarkers and demographic variables is required to establish reliable cut-offs for Alzheimer's disease diagnosis (AD).
Class balancing diversity multimodal ensemble for Alzheimer's disease diagnosis and early detection.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 22, 2025
Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection and diagnosis of AD are critical for delaying progression and improving patient outcomes. Traditional ...
Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 22, 2025
BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes a...
Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.
EBioMedicine
Mar 22, 2025
BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology an...
Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007-2018.
BMJ open
Mar 22, 2025
OBJECTIVES: This study aimed to compare the performance of five machine learning algorithms to predict diabetes mellitus based on lifestyle factors (diet and physical activity).
Machine learning-based model for predicting all-cause mortality in severe pneumonia.
BMJ open respiratory research
Mar 22, 2025
BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such as Acute Physiology and Chronic Health Evaluation (APACHE-II) and Sequential Organ Failure Assessment (SOFA), have limited ability to help clinicians i...
Bioinformatics and machine learning approaches to explore key biomarkers in muscle aging linked to adipogenesis.
BMC musculoskeletal disorders
Mar 22, 2025
Adipogenesis is intricately linked to the onset and progression of muscle aging; however, the relevant biomarkers remain unclear. This study sought to identify key genes associated with adipogenesis in the context of muscle aging. Firstly, gene expre...
Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients.
BMC geriatrics
Mar 22, 2025
BACKGROUND: Depression is a common complication after a stroke that may lead to increased disability and decreased quality of life. The objective of this study was to develop and validate an interpretable predictive model to assess the risk of depres...
Optimizing heart disease diagnosis with advanced machine learning models: a comparison of predictive performance.
BMC cardiovascular disorders
Mar 22, 2025
Cardiovascular disease is the leading cause of mortality globally, necessitating precise and prompt predictive instruments to enhance patient outcomes. In recent years, machine learning methodologies have demonstrated significant potential in enhanci...
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