AIMC Topic: Machine Learning

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Machine-Learning-Based Prediction of a Missed Scheduled Clinical Appointment by Patients With Diabetes.

Journal of diabetes science and technology
BACKGROUND: About 10% of patients with diabetes discontinue treatment, resulting in the progression of diabetes-related complications and reduced quality of life.

Parsimonious kernel extreme learning machine in primal via Cholesky factorization.

Neural networks : the official journal of the International Neural Network Society
Recently, extreme learning machine (ELM) has become a popular topic in machine learning community. By replacing the so-called ELM feature mappings with the nonlinear mappings induced by kernel functions, two kernel ELMs, i.e., P-KELM and D-KELM, are ...

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

Database : the journal of biological databases and curation
We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Pa...

Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis.

PloS one
OBJECTIVES: 1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop a...

Extensions to a manifold learning framework for time-series analysis on dynamic manifolds in bioelectric signals.

Physical review. E
This paper addresses the challenge of extracting meaningful information from measured bioelectric signals generated by complex, large scale physiological systems such as the brain or the heart. We focus on a combination of the well-known Laplacian ei...

A review of the applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles.

Computer methods and programs in biomedicine
This article presents a comprehensive review of applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles of medical interest. The papers reviewed here present the results of research using these te...

Meta-cognitive online sequential extreme learning machine for imbalanced and concept-drifting data classification.

Neural networks : the official journal of the International Neural Network Society
In this paper, a meta-cognitive online sequential extreme learning machine (MOS-ELM) is proposed for class imbalance and concept drift learning. In MOS-ELM, meta-cognition is used to self-regulate the learning by selecting suitable learning strategie...

Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The paradigm of simultaneous and proportional myocontrol of hand prostheses is gaining momentum in the rehabilitation robotics community. As opposed to the traditional surface electromyography classification schema, in simultaneous and proportional c...

Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identifying disease-mutation relationships is a significant challenge in the advancement of precision medicine. The aim of this work is to design a tool that automates the extraction of disease-related mutations from biomedical text to adv...

Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: (1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-w...