AIMC Topic: Missouri
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Application of Machine Learning and Deep Neural Visual Features for Predicting Adult Obesity Prevalence in Missouri.
International journal of environmental research and public health
Nov 19, 2024
This research study investigates and predicts the obesity prevalence in Missouri, utilizing deep neural visual features extracted from medium-resolution satellite imagery (Sentinel-2). By applying a deep convolutional neural network (DCNN), the study...
Deep-learning model for predicting 30-day postoperative mortality.
British journal of anaesthesia
Sep 23, 2019
BACKGROUND: Postoperative mortality occurs in 1-2% of patients undergoing major inpatient surgery. The currently available prediction tools using summaries of intraoperative data are limited by their inability to reflect shifting risk associated with...
Initial report of safety and procedure duration of robotic-assisted chronic total occlusion coronary intervention.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Sep 4, 2019
BACKGROUND: No previous reports have examined the impact of robotic-assisted (RA) chronic total occlusion (CTO) PCI on procedural duration or safety compared to totally manual CTO PCI.
Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study.
BMJ open
Apr 10, 2018
INTRODUCTION: Mortality and morbidity following surgery are pressing public health concerns in the USA. Traditional prediction models for postoperative adverse outcomes demonstrate good discrimination at the population level, but the ability to forec...
Development and evaluation of a 4M taxonomy from nursing home staff text messages using a fine-tuned generative language model.
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2025
OBJECTIVE: This study aimed to explore the utilization of a fine-tuned language model to extract expressions related to the Age-Friendly Health Systems 4M Framework (What Matters, Medication, Mentation, and Mobility) from nursing home worker text mes...
Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.
Studies in health technology and informatics
Aug 21, 2019
Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity...
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