AIMC Topic: Middle Aged
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A plasma metabolome-derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank.
Diabetes, obesity & metabolism
Jun 11, 2025
AIMS: Severe liver disease (SLD) in nonalcoholic fatty liver disease (NAFLD) is often diagnosed late due to the long asymptomatic period of progressive fibrosis. We aimed to identify metabolomic profiles associated with SLD and develop a predictive m...
Evaluation of semi-automated versus fully automated technologies for computed tomography scalable body composition analyses in patients with severe acute respiratory syndrome Coronavirus-2.
Clinical nutrition ESPEN
Jun 11, 2025
RATIONALE AND OBJECTIVES: Fully automated, artificial intelligence (AI) -based software has recently become available for scalable body composition analysis. Prior to broad application in the clinical arena, validation studies are needed. Our goal wa...
Identification of neurological text markers associated with risk of stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jun 11, 2025
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...
Stroke
Data Mining
Academic Medical Centers
Time Factors
Predictive Value of Tests
Natural Language Processing
Emergency Service, Hospital
Humans
Electronic Health Records
Prognosis
Female
Retrospective Studies
Reproducibility of Results
Risk Factors
Aged
Male
Aged, 80 and over
Middle Aged
Risk Assessment
Towards more reliable prostate cancer detection: Incorporating clinical data and uncertainty in MRI deep learning.
Computers in biology and medicine
Jun 11, 2025
Prostate cancer (PCa) is one of the most common cancers among men, and artificial intelligence (AI) is emerging as a promising tool to enhance its diagnosis. This work proposes a classification approach for PCa cases using deep learning techniques. W...
Identifying patients at risk of increased health utilization following lumbar spine surgery.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 11, 2025
BACKGROUND: Adequate preoperative identification of patients at risk of significant healthcare utilization after surgery could help guide preoperative decision-making as well as postoperative patient management. While several studies have proposed me...
A lipid atlas of the human kidney.
Science advances
Jun 11, 2025
Tissue atlases provide foundational knowledge on the cellular organization and molecular distributions across molecular classes and spatial scales. Here, we construct a comprehensive spatiomolecular lipid atlas of the human kidney from 29 donor tissu...
Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study.
Journal of medical Internet research
Jun 11, 2025
BACKGROUND: Implementing machine learning models to identify clinical deterioration in the wards is associated with decreased morbidity and mortality. However, these models have high false positive rates and only use structured data.
28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.
Clinical and experimental medicine
Jun 11, 2025
To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained fro...
Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.
Techniques in coloproctology
Jun 11, 2025
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...
Next-Generation Sequencing-Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods.
JMIR cancer
Jun 11, 2025
BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines for patients with advanced or metastatic disease.
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