AIMC Topic: Machine Learning

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Adaptive detrending to accelerate convolutional gated recurrent unit training for contextual video recognition.

Neural networks : the official journal of the International Neural Network Society
Video image recognition has been extensively studied with rapid progress recently. However, most methods focus on short-term rather than long-term (contextual) video recognition. Convolutional recurrent neural networks (ConvRNNs) provide robust spati...

Fine-grained leukocyte classification with deep residual learning for microscopic images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past developm...

A machine learning based approach to identify protected health information in Chinese clinical text.

International journal of medical informatics
BACKGROUND: With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of id...

Minimization of annotation work: diagnosis of mammographic masses via active learning.

Physics in medicine and biology
The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In ...

Relationships Between the External and Internal Training Load in Professional Soccer: What Can We Learn From Machine Learning?

International journal of sports physiology and performance
PURPOSE: Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators (ELIs) and the rating of perceived exertion (R...

Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
Automatically extracting the relationships between chemicals and diseases is significantly important to various areas of biomedical research and health care. Biomedical experts have built many large-scale knowledge bases (KBs) to advance the developm...

Comparison of variable selection methods for clinical predictive modeling.

International journal of medical informatics
OBJECTIVE: Modern machine learning-based modeling methods are increasingly applied to clinical problems. One such application is in variable selection methods for predictive modeling. However, there is limited research comparing the performance of cl...

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

Journal of neural engineering
OBJECTIVE: Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usabil...

Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods.

Journal of chemical information and modeling
Drug metabolism is a complex procedure in the human body, including a series of enzymatically catalyzed reactions. However, it is costly and time consuming to investigate drug metabolism experimentally; computational methods are hence developed to pr...