AIMC Topic: Adult

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Shoulder Musculoskeletal Disorder Rehabilitation Using a Robotic Device Based on Electromyography (EMG) Biofeedback: A Retrospective Cohort Study.

Medicina (Kaunas, Lithuania)
: While shoulder injuries represent the musculoskeletal disorders (MSDs) most encountered in physical therapy, there is no consensus on their management. In attempts to provide standardized and personalized treatment, a robotic-assisted device combin...

Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset.

BMC medical informatics and decision making
BACKGROUND: Medical imaging techniques for diagnosing sarcopenia have been extensively investigated. Studies have proposed using the T-score and patient information as key diagnostic factors. However, these techniques have either been time-consuming ...

Ensemble learning to predict short birth interval among reproductive-age women in Ethiopia: evidence from EDHS 2016-2019.

BMC pregnancy and childbirth
BACKGROUND: A birth interval of less than 33 months was considered short, and in low- income countries like Ethiopia, a short birth interval is the primary cause of approximately 822 maternal deaths every day. Due to that this study aimed to predict ...

Predictors of depression among Chinese college students: a machine learning approach.

BMC public health
BACKGROUND: Depression is highly prevalent among college students, posing a significant public health challenge. Identifying key predictors of depression is essential for developing effective interventions. This study aimed to analyze potential depre...

Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements.

Scientific reports
Chronic kidney disease (CKD) is a global health concern with early detection playing a pivotal role in effective management. Machine learning models demonstrate promise in CKD detection, yet the impact on detection and classification using different ...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

Scientific reports
This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to predict systemic inflammatory response syndrome (SIRS) after endoscopic surgery for kidney stones. The goal is to identify high-risk patients early and p...

Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study.

JMIR medical informatics
BACKGROUND: Modern lifestyle risk factors, like physical inactivity and poor nutrition, contribute to rising rates of obesity and chronic diseases like type 2 diabetes and heart disease. Particularly personalized interventions have been shown to be e...

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study.

JMIR formative research
BACKGROUND: The COVID-19 pandemic has significantly strained health care systems globally, leading to an overwhelming influx of patients and exacerbating resource limitations. Concurrently, an "infodemic" of misinformation, particularly prevalent in ...

Age-stratified deep learning model for thyroid tumor classification: a multicenter diagnostic study.

European radiology
OBJECTIVES: Thyroid cancer, the only cancer that uses age as a specific predictor of survival, is increasing in incidence, yet it has a low mortality rate, which can lead to overdiagnosis and overtreatment. We developed an age-stratified deep learnin...

Habitat-Based Radiomics for Revealing Tumor Heterogeneity and Predicting Residual Cancer Burden Classification in Breast Cancer.

Clinical breast cancer
PURPOSE: To investigate the feasibility of characterizing tumor heterogeneity in breast cancer ultrasound images using habitat analysis technology and establish a radiomics machine learning model for predicting response to neoadjuvant chemotherapy (N...