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Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports
Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we have collected information on 2572 subjects and used generalized linear model to investigate the association between urinary heavy metal levels and g...

Contrast-enhanced magnetic resonance imaging based calf muscle perfusion and machine learning in peripheral artery disease.

Scientific reports
Peripheral artery disease (PAD) remains underdiagnosed and undertreated and is associated with an increased risk for adverse cardiovascular outcomes. Imaging provides an approach to identifying patients with PAD. However, the role of integrating imag...

Biopsychosocial based machine learning models predict patient improvement after total knee arthroplasty.

Scientific reports
Total knee arthroplasty (TKA) is an effective treatment for end stage osteoarthritis. However, biopsychosocial features are not routinely considered in TKA clinical decision-making, despite increasing evidence to support their role in patient recover...

Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics.

Scientific reports
Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been integrated into clinical practice. This study explores the feasibility of combining deep learning and pathomics to identify tumor invasiveness in LUAD pa...

Physician Perspectives on the Potential Benefits and Risks of Applying Artificial Intelligence in Psychiatric Medicine: Qualitative Study.

JMIR mental health
BACKGROUND: As artificial intelligence (AI) tools are integrated more widely in psychiatric medicine, it is important to consider the impact these tools will have on clinical practice.

Discrepancies between physician-assessed and patient-reported complications after cystectomy - a prospective analysis.

World journal of urology
PURPOSE: Despite the high incidence of perioperative complications following cystectomy, there is a lack of evidence regarding patients' perceptions. Moreover, discrepancies between established complication grading systems and the patient's perspecti...

Human sleep position classification using a lightweight model and acceleration data.

Sleep & breathing = Schlaf & Atmung
PURPOSE: This exploratory study introduces a portable, wearable device using a single accelerometer to monitor twelve sleep positions. Targeted for home use, the device aims to assist patients with mild conditions such as gastroesophageal reflux dise...

Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging.

Scientific reports
Ensemble learning can effectively mitigate the risk of model overfitting during training. This study aims to evaluate the performance of ensemble learning models in predicting tumor deposits in rectal cancer (RC) and identify the optimal model for pr...

Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.

IEEE journal of biomedical and health informatics
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for localizing the seizure onset zone (SOZ) in patients with focal refractory epilepsy. Despite their clinical significance, HFO analysis is often compro...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

IEEE journal of biomedical and health informatics
Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruit...