IEEE transactions on bio-medical engineering
Nov 21, 2024
The severity of mobility deficits is one of the most critical parameters in the diagnosis of Parkinson's disease (PD) and rehabilitation. The current approach for severity evaluation is clinical scaling that relies on a clinician's subjective observa...
BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies investigating the relationship between oxidative stress and prognosis of elderly patients with esophagea...
BACKGROUND: Suicidal behaviors, which may lead to death (suicide) or survival (suicide attempt), are influenced by various factors. Identifying the specific risk factors for suicidal behavior mortality is critical for improving prevention strategies ...
BACKGROUND AND OBJECTIVE: Detecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decisi...
INTRODUCTION: Implementing artificial intelligence (AI) in healthcare, particularly in primary care settings, raises crucial questions about practical challenges and opportunities. This study aimed to explore the perspectives of general practitioners...
Computer methods and programs in biomedicine
Nov 20, 2024
INTRODUCTION: Prostate cancer remains a significant health concern, with radical prostatectomy being a common treatment approach. However, predicting postoperative functional outcomes, particularly urinary continence and erectile function, poses chal...
OBJECTIVE: To investigate the association between systemic sclerosis (SSc) clinical features and the extent and progression of coronary artery calcifications.
The study explored endocrine resistance by leveraging machine learning to establish the prognostic stratification of predicted Circulating tumor cells (CTCs), assessing its integration with circulating tumor DNA (ctDNA) features and contextually eval...
Journal of the American College of Cardiology
Nov 20, 2024
BACKGROUND: Predicting the clinical trajectory of individual patients with implantable cardioverter-defibrillators (ICDs) is essential to inform clinical care. Machine learning approaches can potentially overcome the limitations of conventional stati...
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