To investigate the perioperative outcomes of patients who underwent robot-assisted thoracoscopic (RATS) segmentectomy for identifying the intersegmental plane (ISP) by improved modified inflation-deflation (MID) combined with near-infrared fluorescen...
PURPOSE: To report the trends, predictors, and patient outcomes of same-day discharge (SDD) versus non-SDD for robot-assisted laparoscopic radical prostatectomy (RALP).
Journal of cardiovascular electrophysiology
Jun 5, 2023
INTRODUCTION: The advancement of artificial intelligence (AI) has aided clinicians in the interpretation of electrocardiograms (ECGs) serving as an essential tool to provide rapid triage and care. However, in some cases, AI can misinterpret an ECG an...
: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for early diagnosis and improved patient outcomes. The purpose of this study is to explore the deep-lea...
BACKGROUND: The COVID-19 pandemic has led to an unprecedented amount of scientific publications, growing at a pace never seen before. Multiple living systematic reviews have been developed to assist professionals with up-to-date and trustworthy healt...
Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this study, we assessed their impact on cerebrovascular flow volume measurements, evaluated the benefit of manual image-based correction, and assessed the pote...
IEEE journal of biomedical and health informatics
Jun 5, 2023
During COVID-19 pandemic qRT-PCR, CT scans and biochemical parameters were studied to understand the patients' physiological changes and disease progression. There is a lack of clear understanding of the correlation of lung inflammation with biochemi...
RATIONALE AND OBJECTIVES: Fluid-attenuated inversion recovery (FLAIR) imaging is playing an increasingly significant role in the detection of brain metastases with a concomitant increase in the number of magnetic resonance imaging (MRI) examinations....
PURPOSE: This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI).
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