AI Medical Compendium Topic:
Databases, Factual

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Identification of prognostic factors for pediatric myocarditis with a random forests algorithm-assisted approach.

Pediatric research
BACKGROUND: Pediatric myocarditis is a rare disease with substantial mortality. Little is known regarding its prognostic factors. We hypothesize that certain comorbidities and procedural needs may increase risks of poor outcomes. This study aims to i...

Joint Local and Global Information Learning With Single Apex Frame Detection for Micro-Expression Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Micro-expressions (MEs) are rapid and subtle facial movements that are difficult to detect and recognize. Most recent works have attempted to recognize MEs with spatial and temporal information from video clips. According to psychological studies, th...

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SS...

Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Detecting human parts at instance-level is an essential prerequisite for the analysis of human keypoints, actions, and attributes. Nonetheless, there is a lack of a large-scale, rich-annotated dataset for human parts detection. We fill in the gap by ...

Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning.

Nature communications
Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we u...

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

PloS one
A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) provided 799233 complete patient records (778303 survivors and 20930 deaths) each containing 32 featur...

Machine Learning Methods in Drug Discovery.

Molecules (Basel, Switzerland)
The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been use...

An integrative knowledge graph for rare diseases, derived from the Genetic and Rare Diseases Information Center (GARD).

Journal of biomedical semantics
BACKGROUND: The Genetic and Rare Diseases (GARD) Information Center was established by the National Institutes of Health (NIH) to provide freely accessible consumer health information on over 6500 genetic and rare diseases. As the cumulative scientif...

Efficient architecture for deep neural networks with heterogeneous sensitivity.

Neural networks : the official journal of the International Neural Network Society
In this study, we present a neural network that consists of nodes with heterogeneous sensitivity. Each node in a network is assigned a variable that determines the sensitivity with which it learns to perform a given task. The network is trained via a...

FMixCutMatch for semi-supervised deep learning.

Neural networks : the official journal of the International Neural Network Society
Mixed sample augmentation (MSA) has witnessed great success in the research area of semi-supervised learning (SSL) and is performed by mixing two training samples as an augmentation strategy to effectively smooth the training space. Following the ins...