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Mapping Patient Trajectories using Longitudinal Extraction and Deep Learning in the MIMIC-III Critical Care Database.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health ...

Population-Based Analysis of Histologically Confirmed Melanocytic Proliferations Using Natural Language Processing.

JAMA dermatology
IMPORTANCE: Population-based information on the distribution of histologic diagnoses associated with skin biopsies is unknown. Electronic medical records (EMRs) enable automated extraction of pathology report data to improve our epidemiologic underst...

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution.

Clinical and translational science
Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are commonly utilized to gather additional clinical data elements needed for translational research. Howev...

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

Annals of the American Thoracic Society
RATIONALE: Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based o...

Smooth leader or sharp follower? Playing the mirror game with a robot.

Restorative neurology and neuroscience
BACKGROUND: The increasing number of opportunities for human-robot interactions in various settings, from industry through home use to rehabilitation, creates a need to understand how to best personalize human-robot interactions to fit both the user ...

Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions.

Journal for healthcare quality : official publication of the National Association for Healthcare Quality
A diverse universe of statistical models in the literature aim to help hospitals understand the risk factors of their preventable readmissions. However, these models are usually not necessarily applicable in other contexts, fail to achieve good discr...

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects ...

Clinical manifestation of malignant lymphomas of the head and neck region.

Otolaryngologia polska = The Polish otolaryngology
INTRODUCTION: Malignant lymphoma (ML) is a neoplasm caused by clonal expansion of undifferentiated B, T and NK-lymphoid cells. WHO classification divides lymphomas into two main types, i.e. Hodgkin lymphoma (HL), and non-Hodgkin lymphoma (NHL), with ...