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Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.
Surgery
Mar 23, 2025
BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic regression in forecasting discharge against medical advice occurrences needs to be evaluated.
Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts.
Computers in biology and medicine
Mar 23, 2025
BACKGROUND: This study develops a deep learning-based automated lesion segmentation model for whole-body 3DF-fluorodeoxyglucose (FDG)-Position emission tomography (PET) with computed tomography (CT) images agnostic to disease location and site.
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 ...
AI Efficiency in Dentistry: Comparing Artificial Intelligence Systems with Human Practitioners in Assessing Several Periodontal Parameters.
Medicina (Kaunas, Lithuania)
Mar 23, 2025
Artificial intelligence (AI) is increasingly used in healthcare, including dental and periodontal diagnostics, due to its ability to analyze complex datasets with speed and precision. This study aimed to evaluate the reliability of AI-assisted denta...
Integration of AI lesion classification, age, and BI-RADS assessment to reduce benign biopsies on breast ultrasound.
European radiology
Mar 22, 2025
OBJECTIVES: To develop and test AI-integrated biopsy avoidance strategies to improve the specificity of screening breast ultrasound (US).
A longitudinal observational study with ecological momentary assessment and deep learning to predict non-prescribed opioid use, treatment retention, and medication nonadherence among persons receiving medication treatment for opioid use disorder.
Journal of substance use and addiction treatment
Mar 22, 2025
BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks of adverse outcomes, including death. Predicting important outcomes, including non-prescribed opioid ...
Pharmacy faculty and students perceptions of artificial intelligence: A National Survey.
Currents in pharmacy teaching & learning
Mar 22, 2025
INTRODUCTION: This study explores the perceptions, familiarity, and utilization of artificial intelligence (AI) among pharmacy faculty and students across the United States. By identifying key gaps in AI education and training, it highlights the need...
An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.
Asian journal of psychiatry
Mar 22, 2025
BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these...
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).
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