BACKGROUND: Accurately predicting left ventricular ejection fraction (LVEF) recovery after percutaneous coronary intervention (PCI) in patients with chronic coronary syndrome (CCS) is crucial for clinical decision-making.
BACKGROUND: Wearable devices enable continuous measurement of physical activity, sedentary behavior, sleep, and heart rate under free-living conditions. However, most validation studies rely on small, homogeneous samples; are conducted under laborato...
BACKGROUND: Cisgender lesbian, bisexual, and queer (LBQ+) women of color experience barriers to accessing sexual and reproductive health (SRH) services in the United States. Barriers, including limited provider access and poor patient-provider commun...
BACKGROUND: Preoperative prediction of surgical difficulty in robotic-assisted total mesorectal excision for rectal cancer remains challenging. While pelvic anatomical parameters measured by MRI have been associated with surgical complexity in laparo...
Central nervous system (CNS) involvement in primary Sjögren's syndrome (pSS), although less frequent, can lead to serious complications. Our study aimed to assess white matter (WM) tract integrity, identify specific regions of disruption, quantify di...
This study aimed to develop an artificial intelligence-based classification system using ultrasound images obtained via a transgluteal cleft scanning approach for detecting fecal retention in the lower rectum. The goal was to support accurate, object...
BACKGROUND: Metabolic syndrome (MetS) is characterized by chronic inflammation and can be worsened by circadian disruption, which is common among shift work. Machine learning can predict the risk of MetS in shift workers using inflammatory biomarkers...
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...
Coronary heart disease (CHD) remains the leading cause of mortality worldwide, disproportionately affecting low- and middle-income countries where diagnostic resources are limited. Traditional statistical models often fail to deliver adequate predict...
The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients' blood glucose levels and potential adverse events in advance. This study employs a deep...
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