AIMC Topic: Deep Learning

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Deep learning for prediction of colorectal cancer outcome: a discovery and validation study.

Lancet (London, England)
BACKGROUND: Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal ...

Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Anesthesiology
Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence ...

Artificial intelligence approaches to improve kidney care.

Nature reviews. Nephrology
Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acute and chronic kidney diseases. Studies published in 2019 relied on a variety of available data sources towards this objective, including electronic he...

Using a Dual-Input Convolutional Neural Network for Automated Detection of Pediatric Supracondylar Fracture on Conventional Radiography.

Investigative radiology
OBJECTIVES: This study aimed to develop a dual-input convolutional neural network (CNN)-based deep-learning algorithm that utilizes both anteroposterior (AP) and lateral elbow radiographs for the automated detection of pediatric supracondylar fractur...

Consumer health information and question answering: helping consumers find answers to their health-related information needs.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Consumers increasingly turn to the internet in search of health-related information; and they want their questions answered with short and precise passages, rather than needing to analyze lists of relevant documents returned by search engi...

DeepCOP: deep learning-based approach to predict gene regulating effects of small molecules.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances in the areas of bioinformatics and chemogenomics are poised to accelerate the discovery of small molecule regulators of cell development. Combining large genomics and molecular data sources with powerful deep learning tech...

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT.

Journal of digital imaging
The volume of pelvic hematoma at CT has been shown to be the strongest independent predictor of major arterial injury requiring angioembolization in trauma victims with pelvic fractures, and also correlates with transfusion requirement and mortality....

BioNorm: deep learning-based event normalization for the curation of reaction databases.

Bioinformatics (Oxford, England)
MOTIVATION: A biochemical reaction, bio-event, depicts the relationships between participating entities. Current text mining research has been focusing on identifying bio-events from scientific literature. However, rare efforts have been dedicated to...