AIMC Topic: Social Determinants of Health

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Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.

Journal of medical Internet research
BACKGROUND: Data on the social determinants of health could be used to improve care, support quality improvement initiatives, and track progress toward health equity. However, this data collection is not widespread. Artificial intelligence (AI), spec...

Content Analysis of Social Determinants of Health Accelerator Plans Using Artificial Intelligence: A Use Case for Public Health Practitioners.

Journal of public health management and practice : JPHMP
CONTEXT: Public health practice involves the development of reports and plans, including funding progress reports, strategic plans, and community needs assessments. These documents are valuable data sources for program monitoring and evaluation. Howe...

Social Determinants and Health Equity Activities: Are They Connected with the Adaptation of AI and Telehealth Services in the U.S. Hospitals?

International journal of environmental research and public health
In recent decades, technological shifts within the healthcare sector have significantly transformed healthcare management and utilization, introducing unprecedented possibilities that elevate quality of life. Organizational factors are recognized as ...

Identifying Adolescent Depression and Anxiety Through Real-World Data and Social Determinants of Health: Machine Learning Model Development and Validation.

JMIR mental health
BACKGROUND: The prevalence of adolescent mental health conditions such as depression and anxiety has significantly increased. Despite the potential of machine learning (ML), there is a shortage of models that use real-world data (RWD) to enhance earl...

Scalable information extraction from free text electronic health records using large language models.

BMC medical research methodology
BACKGROUND: A vast amount of potentially useful information such as description of patient symptoms, family, and social history is recorded as free-text notes in electronic health records (EHRs) but is difficult to reliably extract at scale, limiting...

Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Protocol for a Systematic Review.

JMIR research protocols
BACKGROUND: In recent years, the intersection of natural language processing (NLP) and public health has opened innovative pathways for investigating social determinants of health (SDOH) in textual datasets. Despite the promise of NLP in the SDOH dom...

Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review.

JMIR mental health
BACKGROUND: The use of natural language processing (NLP) in mental health research is increasing, with a wide range of applications and datasets being investigated.

A Machine Learning Classification Model for Gastrointestinal Health in Cancer Survivors: Roles of Telomere Length and Social Determinants of Health.

International journal of environmental research and public health
BACKGROUND: Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is crucial for preventing and managing this distress. ...

Extracting social determinants of health from inpatient electronic medical records using natural language processing.

Journal of epidemiology and population health
BACKGROUND: Social determinants of health (SDOH) have been shown to be important predictors of health outcomes. Here we developed methods to extract them from inpatient electronic medical record (EMR) data using techniques compatible with current EMR...