The international journal of cardiovascular imaging
Nov 19, 2020
We developed a machine learning model for efficient analysis of echocardiographic image quality in hospitalized patients. This study applied a machine learning model for automated transthoracic echo (TTE) image quality scoring in three inpatient grou...
Cyberpsychology, behavior and social networking
Nov 18, 2020
Robots are becoming an integral part of society, yet the extent to which we are prosocial toward these nonliving objects is unclear. While previous research shows that we tend to take care of robots in high-risk, high-consequence situations, this has...
Cyberpsychology, behavior and social networking
Nov 18, 2020
Empirical evidence has shown that peer pressure can impact human risk-taking behavior. With robots becoming ever more present in a range of human settings, it is crucial to examine whether robots can have a similar impact. Using the balloon analogue ...
Clinical cancer research : an official journal of the American Association for Cancer Research
Nov 18, 2020
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...
OBJECTIVES: To evaluate a new-generation, non-invasive, wireless axillary thermometer with artificial intelligence, iThermonitor (WT705, Raiing Medical, Beijing, China), and to ascertain its feasibility for perioperative continuous body temperature m...
Chronic tinnitus is a debilitating condition which affects 10-20% of adults and can severely impact their quality of life. Currently there is no objective measure of tinnitus that can be used clinically. Clinical assessment of the condition uses subj...
Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image noise. How the DLR affects image quality and radiation dose reduction has yet to be fully investigated. Purpose To investigate a DLR algorithm's dose redu...
This study aimed to examine whether the diagnostic accuracy of four noninvasive tests (NITs) for detecting advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is maintained or is inferior to with or without the presence of type 2 diabetes. ...
PURPOSE: The purpose of this study is to develop a machine learning algorithm to predict future intubation among patients diagnosed or suspected with COVID-19.
PURPOSE: To demonstrate how artificial intelligence (AI) can expand radiologists' capacity, we visualized the features of invasive ductal carcinomas (IDCs) that our algorithm, developed and validated for basic pathological classification on mammogram...
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