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Contrast-enhanced magnetic resonance imaging based calf muscle perfusion and machine learning in peripheral artery disease.
Scientific reports
Feb 10, 2025
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
Feb 10, 2025
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
Feb 10, 2025
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
Feb 10, 2025
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
Feb 10, 2025
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...
Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging.
Scientific reports
Feb 10, 2025
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...
Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.
IEEE journal of biomedical and health informatics
Feb 10, 2025
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...
RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).
IEEE journal of biomedical and health informatics
Feb 10, 2025
Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant mortality and morbidity among critically ill patients admitted to the Intensive Care Unit (ICU). The etiology related to ARDS can be highly heterogen...
Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.
Circulation. Arrhythmia and electrophysiology
Feb 10, 2025
BACKGROUND: It is difficult to identify patients with atrial fibrillation (AF) most likely to respond to ablation. While any arrhythmia patient may recur after acutely successful ablation, AF is unusual in that patients may have long-term arrhythmia ...
EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.
IEEE journal of biomedical and health informatics
Feb 10, 2025
The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be high if an excessive stimulus is applied to induce the necessary generalized seizure (GS); Conversely, inadequate stimulus results in failure. Recent...
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