AIMC Topic:
Supervised Machine Learning
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Factors influencing unsafe behaviors: A supervised learning approach.
Accident; analysis and prevention
Jun 18, 2018
Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning's advantage in predictive accuracy, this study used a supervised learning approach to evaluate the relative importance of different co...
Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction.
BMC bioinformatics
Jun 13, 2018
BACKGROUND: Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-health monitoring tasks, specifically for pharmacovigilance. We study the problem of extraction of Adve...
Protein-Protein Interactions Prediction via Multimodal Deep Polynomial Network and Regularized Extreme Learning Machine.
IEEE journal of biomedical and health informatics
Jun 12, 2018
Predicting the protein-protein interactions (PPIs) has played an important role in many applications. Hence, a novel computational method for PPIs prediction is highly desirable. PPIs endow with protein amino acid mutation rate and two physicochemica...
Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy.
Breast cancer research and treatment
Jun 6, 2018
BACKGROUND: Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain...
A supervised learning approach for diffusion MRI quality control with minimal training data.
NeuroImage
Jun 5, 2018
Quality control (QC) is a fundamental component of any study. Diffusion MRI has unique challenges that make manual QC particularly difficult, including a greater number of artefacts than other MR modalities and a greater volume of data. The gold stan...
Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.
Journal of neural engineering
Jun 1, 2018
OBJECTIVE: An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practi...
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.
BMC cancer
May 30, 2018
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...
Receptors, Estrogen
Image Processing, Computer-Assisted
Humans
Staining and Labeling
Breast
Breast Neoplasms
Prognosis
Supervised Machine Learning
Young Adult
Principal Component Analysis
Predictive Value of Tests
Models, Biological
Middle Aged
Female
Cell Nucleus
Adult
Risk Factors
Neoplasm Staging
ROC Curve
Genetic Testing
Aged
A System for Automated Determination of Perioperative Patient Acuity.
Journal of medical systems
May 30, 2018
The widely used American Society of Anesthesiologists Physical Status (ASA PS) classification is subjective, requires manual clinician review to score, and has limited granularity. Our objective was to develop a system that automatically generates an...
A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons.
IEEE transactions on neural networks and learning systems
May 28, 2018
Spiking neurons are becoming increasingly popular owing to their biological plausibility and promising computational properties. Unlike traditional rate-based neural models, spiking neurons encode information in the temporal patterns of the transmitt...
Affinity network fusion and semi-supervised learning for cancer patient clustering.
Methods (San Diego, Calif.)
May 26, 2018
Defining subtypes of complex diseases such as cancer and stratifying patient groups with the same disease but different subtypes for targeted treatments is important for personalized and precision medicine. Approaches that incorporate multi-omic data...
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