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Health Records, Personal

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SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes.

BMC bioinformatics
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ont...

Predicting breast cancer risk using personal health data and machine learning models.

PloS one
Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform screening and preventative actions. Previous works found that adding inputs to the widely-used Gail model improved its ability to predict breast cancer ...

Computational prediction of diagnosis and feature selection on mesothelioma patient health records.

PloS one
BACKGROUND: Mesothelioma is a lung cancer that kills thousands of people worldwide annually, especially those with exposure to asbestos. Diagnosis of mesothelioma in patients often requires time-consuming imaging techniques and biopsies. Machine lear...

A sustainable HL7 FHIR based ontology for PHR data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
One of the most widely acknowledged standards in health informatics is HL7 (Health Level 7 International). HL7 FHIR® (Fast Healthcare Interoperability Resources) is a new HL7 standard for exchanging electronic health data. It builds upon previous HL7...

CCMapper: An adaptive NLP-based free-text chief complaint mapping algorithm.

Computers in biology and medicine
OBJECTIVE: Chief complaint (CC) is among the earliest health information recorded at the beginning of a patient's visit to an emergency department (ED). We propose a heuristic methodology for automatically mapping the free-text data into a structured...

Using word embeddings to improve the privacy of clinical notes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In this work, we introduce a privacy technique for anonymizing clinical notes that guarantees all private health information is secured (including sensitive data, such as family history, that are not adequately covered by current technique...