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Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.
Sensors (Basel, Switzerland)
Dec 19, 2024
Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability o...
A Machine Learning Classification Model for Gastrointestinal Health in Cancer Survivors: Roles of Telomere Length and Social Determinants of Health.
International journal of environmental research and public health
Dec 19, 2024
BACKGROUND: Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is crucial for preventing and managing this distress. ...
Machine learning analysis of sex and menopausal differences in the gut microbiome in the HELIUS study.
NPJ biofilms and microbiomes
Dec 19, 2024
Sex differences in the gut microbiome have been examined previously, but results are inconsistent, often due to small sample sizes. We investigated sex and menopausal differences in the gut microbiome in a large multi-ethnic population cohort study, ...
Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation.
Journal of neuroengineering and rehabilitation
Dec 19, 2024
BACKGROUND: Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor disorders. Nevertheless, tasks repetition imposed by robots may induce boredom, affecting clinical outc...
Predictive modeling of ICU-AW inflammatory factors based on machine learning.
BMC neurology
Dec 19, 2024
BACKGROUND: ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used machine learning techniques to construct an ICU-AW inflammatory factor prediction model to predict the risk of disease development and reduce the incidenc...
Detecting cardiovascular diseases using unsupervised machine learning clustering based on electronic medical records.
BMC medical research methodology
Dec 19, 2024
BACKGROUND: Electronic medical records (EMR)-trained machine learning models have the potential in CVD risk prediction by integrating a range of medical data from patients, facilitate timely diagnosis and classification of CVDs. We tested the hypothe...
Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.
BMC cardiovascular disorders
Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.
BMC anesthesiology
Dec 19, 2024
AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) transfusion during hip fracture surgery.
Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study.
Journal of medical Internet research
Dec 19, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by frequent pauses or shallow breathing during sleep. Polysomnography, the gold standard for OSA assessment, is time consuming and labor intensive, thus limiting di...
A Machine Learning-Based Prediction Model for Acute Kidney Injury in Patients With Community-Acquired Pneumonia: Multicenter Validation Study.
Journal of medical Internet research
Dec 19, 2024
BACKGROUND: Acute kidney injury (AKI) is common in patients with community-acquired pneumonia (CAP) and is associated with increased morbidity and mortality.
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