AIMC Topic: Pattern Recognition, Automated

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Prediction the Substrate Specificities of Membrane Transport Proteins Based on Support Vector Machine and Hybrid Features.

IEEE/ACM transactions on computational biology and bioinformatics
Membrane transport proteins and their substrate specificities play crucial roles in a variety of cellular functions. Identifying the substrate specificities of membrane transport proteins is closely related to the protein-target interaction predictio...

Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

IEEE transactions on cybernetics
The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than ...

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM.

PloS one
This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slo...

Close Human Interaction Recognition Using Patch-Aware Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper addresses the problem of recognizing human interactions with close physical contact from videos. Due to ambiguities in feature-to-person assignments and frequent occlusions in close interactions, it is difficult to accurately extract the i...

Automated Extraction of Substance Use Information from Clinical Texts.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural langua...

A Study of Neural Word Embeddings for Named Entity Recognition in Clinical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clinical Named Entity Recognition (NER) is a critical task for extracting important patient information from clinical text to support clinical and translational research. This study explored the neural word embeddings derived from a large unlabeled c...

Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clinical concept recognition (CCR) is a fundamental task in clinical natural language processing (NLP) field. Almost all current machine learning-based CCR systems can only recognize clinical concepts of consecutive words (called consecutive clinical...

Analyzing depression tendency of web posts using an event-driven depression tendency warning model.

Artificial intelligence in medicine
OBJECTIVE: The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining te...

N3 and BNN: Two New Similarity Based Classification Methods in Comparison with Other Classifiers.

Journal of chemical information and modeling
Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbors), are proposed. Both methods are inspired by the principles of the K-nearest neighbors (KNN) method, being both based on object pairwise similarities....