AIMC Topic: Machine Learning

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Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Accurately estimating performance accuracy of machine learning classifiers is of fundamental importance in biomedical research with potentially societal consequences upon the deployment of bestperforming tools in everyday life. Although classificatio...

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The proliferation of healthcare data has brought the opportunities of applying data-driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting...

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical informatics. Increasingly, electronic phenotyping is performed via supervis...

Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Biomedical association studies are increasingly done using clinical concepts, and in particular diagnostic codes from clinical data repositories as phenotypes. Clinical concepts can be represented in a meaningful, vector space using word embedding mo...

Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning.

Methods in molecular biology (Clifton, N.J.)
The creation of big clinical data cohorts for machine learning and data analysis require a number of steps from the beginning to successful completion. Similar to data set preprocessing in other fields, there is an initial need to complete data quali...

Computer-Assisted Wound Assessment and Care Education Program in Registered Nurses: Use of an Interactive Online Program by 418 Registered Nurses.

Journal of wound, ostomy, and continence nursing : official publication of The Wound, Ostomy and Continence Nurses Society
PURPOSE: The purpose of this descriptive study was to evaluate use of a previously validated, online, interactive wound assessment and wound care clinical pathway in a group of RNs. Specific aims were to (a) evaluate the proportions of correct, parti...

Artificial Intelligence and Radiology in Singapore: Championing a New Age of Augmented Imaging for Unsurpassed Patient Care.

Annals of the Academy of Medicine, Singapore
Artificial intelligence (AI) has been positioned as being the most important recent advancement in radiology, if not the most potentially disruptive. Singapore radiologists have been quick to embrace this technology as part of the natural progression...

Data Profiling in Support of Entity Resolution of Multi-Institutional EHR Data.

Studies in health technology and informatics
Information Quality (IQ) is a core tenant of contemporary data management practices. Across many disciplines and industries, it has become a necessary process to improve value and reduce liability in data driven processes. Information quality is a mu...

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Integrative biology : quantitative biosciences from nano to macro
Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and prov...