Journal of vascular and interventional radiology : JVIR
May 4, 2020
PURPOSE: To demonstrate that random forest models trained on a large national sample can accurately predict relevant outcomes and may ultimately contribute to future clinical decision support tools in IR.
Proceedings of the National Academy of Sciences of the United States of America
May 4, 2020
Replicability tests of scientific papers show that the majority of papers fail replication. Moreover, failed papers circulate through the literature as quickly as replicating papers. This dynamic weakens the literature, raises research costs, and dem...
This study aimed to develop a diagnostic algorithm for preoperative differentiating uterine sarcoma from leiomyoma through a supervised machine-learning method using multi-parametric MRI. A total of 65 participants with 105 myometrial tumors were inc...
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...
All living systems are maintained by a constant flux of metabolic energy and, among the different reactions, the process of lipids storage and lipolysis is of fundamental importance. Current research has focused on the investigation of lipid droplets...
Emergence of new disease remains a critical parameter in human health and society. Advances in artificial intelligence (AI) allow for rapid processing and analysis of massive and complex data. In this forum article, the recent applications across dis...
Journal of computer-aided molecular design
May 2, 2020
Difficulties in interpreting machine learning (ML) models and their predictions limit the practical applicability of and confidence in ML in pharmaceutical research. There is a need for agnostic approaches aiding in the interpretation of ML models re...
In this study, we propose a method for training convolutional neural networks to make them identify and classify images with higher classification accuracy. By combining the Cartesian and polar coordinate systems when describing the images, the metho...
BACKGROUND: The decision to treat unruptured intracranial aneurysms (UIAs) or not is complex and requires balancing of risk factors and scores. Machine learning (ML) algorithms have previously been effective at generating highly accurate and comprehe...
Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to cha...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.