PURPOSE: The purpose of this study was to validate the accuracy of an artificial intelligence (AI) prototype application in determining bone mineral density (BMD) from chest computed tomography (CT), as compared with dual-energy x-ray absorptiometry ...
BACKGROUND: Prognostic modeling in health care has been predominantly statistical, despite a rapid growth of literature on machine-learning approaches in biological data analysis. We aim to assess the relative importance of variables in predicting ov...
OBJECTIVES: The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).
We report the use of a bone-anchored, self-contained robotic arm with both sensory and motor components over 3 to 7 years in four patients after transhumeral amputation. The implant allowed for bidirectional communication between a prosthetic hand an...
Clinical and translational gastroenterology
Apr 1, 2020
OBJECTIVES: We lack reliable methods for identifying patients with chronic pancreatitis (CP) at increased risk for pancreatic cancer. We aimed to identify radiographic parameters associated with pancreatic cancer in this population.
Topics in magnetic resonance imaging : TMRI
Apr 1, 2020
This manuscript will review emerging applications of artificial intelligence, specifically deep learning, and its application to glioblastoma multiforme (GBM), the most common primary malignant brain tumor. Current deep learning approaches, commonly ...
OBJECTIVE: Among western males, prostate cancer is the most frequent oncological disease. Since the widespread of PSA, diagnoses in younger adults is increasing. The aim of this study is to analyze pathological features and biochemical recurrence eve...
OBJECTIVE: Despite numerous imaging studies highlighting the importance of the thalamus in a patient's surgical prognosis, human electrophysiological studies involving the limbic thalamic nuclei are limited. The objective of this study was to evaluat...
OBJECTIVES: As the performance of a conventional track and trigger system in a rapid response system has been unsatisfactory, we developed and implemented an artificial intelligence for predicting in-hospital cardiac arrest, denoted the deep learning...
UNLABELLED: PRéCIS:: A spectral-domain optical coherence tomography (SD-OCT) based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminatin...
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