Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) remains a major concern in deceased donor kidney transplantation (DDKT). To this end, we harnessed ML t...
Diagnosis of endoleak following endovascular aortic repair (EVAR) relies on manual review of multi-slice CT angiography (CTA) by physicians which is a tedious and time-consuming process that is susceptible to error. We evaluate the use of a deep neur...
OBJECTIVE: To determine how machine learning has been applied to prediction applications in population health contexts. Specifically, to describe which outcomes have been studied, the data sources most widely used and whether reporting of machine lea...
BMC medical informatics and decision making
Oct 27, 2020
BACKGROUND: Severe sepsis and septic shock are among the leading causes of death in the United States and sepsis remains one of the most expensive conditions to diagnose and treat. Accurate early diagnosis and treatment can reduce the risk of adverse...
PURPOSE: We used five machine-learning algorithms to predict cancer-specific mortality after surgical resection of primary non-metastatic invasive breast cancer.
Diagnostic and interventional imaging
Oct 26, 2020
The application of machine learning and deep learning in the field of imaging is rapidly growing. Although the principles of machine and deep learning are unfamiliar to the majority of clinicians, the basics are not so complicated. One of the major i...
The journal of physical chemistry letters
Oct 26, 2020
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...
Biological contextual information helps understand various phenomena occurring in the biological systems consisting of complex molecular relations. The construction of context-specific relational resources vastly relies on laborious manual extraction...
BACKGROUND: Federated learning (FL) is a newly proposed machine-learning method that uses a decentralized dataset. Since data transfer is not necessary for the learning process in FL, there is a significant advantage in protecting personal privacy. T...
It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this study was to develop and validate an automated identification of postural control patterns in children ...
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