AIMC Topic: Social Determinants of Health

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A marker-based neural network system for extracting social determinants of health.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The impact of social determinants of health (SDoH) on patients' healthcare quality and the disparity is well known. Many SDoH items are not coded in structured forms in electronic health records. These items are often captured in free-text...

The 2022 n2c2/UW shared task on extracting social determinants of health.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The n2c2/UW SDOH Challenge explores the extraction of social determinant of health (SDOH) information from clinical notes. The objectives include the advancement of natural language processing (NLP) information extraction techniques for SD...

Extracting social determinants of health from electronic health records using natural language processing: a systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social determinants of health (SDoH) are nonclinical dispositions that impact patient health risks and clinical outcomes. Leveraging SDoH in clinical decision-making can potentially improve diagnosis, treatment planning, and patient outcom...

Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.

Journal of the American Medical Informatics Association : JAMIA
Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health care. Given their intended placement within healthcare decision making more broadly, ML tools require a...

Identifying Patients with Significant Problems Related to Social Determinants of Health with Natural Language Processing.

Studies in health technology and informatics
Social and behavioral factors influence health but are infrequently recorded in electronic health records (EHRs). Here, we demonstrate that psychosocial vital signs can be extracted from EHR data. We processed structured and unstructured EHR data usi...

Enrich classifications in psychiatry with textual data: an ontology for psychiatry including social concepts.

Studies in health technology and informatics
We propose a modular approach to develop an ontology of psychiatry, ONTOPSYCHIA, based on Patient Discharges Summaries (PDS) and divided into three modules (i.e. social, mental disorders and treatments). We decided to take into account the social asp...