ArticleHealth services research2023
Natural language processing to identify social determinants of health in Alzheimer's disease and related dementia from electronic health records.
Article in Health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Natural language processing for geriatric syndromes: a systematic review of methods, applications, and challenges.BMC medical informatics and decision making · 2026Pooled it
- Posttraumatic Stress Disorder, Health-Related Social Needs, and Cognitive Outcomes in US Veterans.JAMA network open · 2026Article
- Article
- A novel computational analysis integrating social determinants information from EHR and literature with Alzheimer's disease biological knowledge through large language models and knowledge graphs.Innovation in aging · 2025Article
- Machine learning approaches to racial/ethnic differences in social determinants of mild cognitive impairment and its progression to dementia in the All of Us Research Program.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- Predicting Behavioral Determinants of Health from Clinical Text Using Transformer Models and BiLSTM.medRxiv : the preprint server for health sciences · 2025Article
- SBDH-Reader: a large language model-powered method for extracting social and behavioral determinants of health from clinical notes.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study.JMIR medical informatics · 2025Article
- Extracting Social Determinants of Health from Dental Clinical Notes.Applied clinical informatics · 2025Article
- Development of a natural language processing algorithm to extract social determinants of health from clinician notes.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2025Article
- Extracting Housing and Food Insecurity Information From Clinical Notes Using cTAKES.Health services research · 2025Article
- Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Protocol for a Systematic Review.JMIR research protocols · 2025Article
- Using large language models for extracting stressful life events to assess their impact on preventive colon cancer screening adherence.BMC public health · 2025Article
- Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Model-based estimation of individual-level social determinants of health and its applications in All of Us.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- On the development and validation of large language model-based classifiers for identifying social determinants of health.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Extracting Critical Information from Unstructured Clinicians' Notes Data to Identify Dementia Severity Using a Rule-Based Approach: Feasibility Study.JMIR aging · 2024Article
- Predicting Risk of Alzheimer's Diseases and Related Dementias with AI Foundation Model on Electronic Health Records.medRxiv : the preprint server for health sciences · 2024Article
- Natural language processing to identify social determinants of health in Alzheimer's disease and related dementia from electronic health records.Health services research · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo develop a natural language processing (NLP) algorithm that identifies social determinants of health (SDoH), including housing, transportation, food, and medication insecurities, social isolation, abuse, neglect, or exploitation, and financial difficulties for patients with Alzheimer's disease and related dementias (ADRD) from unstructured electronic health records (EHRs). DATA SOURCES AND STUDY
settingWe leveraged 1000 medical notes randomly selected from 7401 emergency department and inpatient social worker notes generated between 2015 and 2019 for 231 unique patients diagnosed with ADRD at Michigan Medicine. STUDY
designWe developed a rule-based NLP algorithm for the identification of seven domains of SDoH noted above. We also compared the rule-based algorithm with deep learning and regularized logistic regression approaches. These models were compared using accuracy, sensitivity, specificity, F1 score, and the area under the receiver operating characteristic curve (AUC). All notes were split into 700 notes for training NLP algorithms, and 300 notes for validation. DATA COLLECTION/EXTRACTION
methodsSocial worker notes used in this study were extracted from the Michigan Medicine EHR database. PRINCIPAL
findingsOf the 700 notes for training, F1 and AUC for the rule-based algorithm were at least 0.94 and 0.95, respectively, for all SDoH categories. Of the 300 notes for validation, F1 and AUC were at least 0.80 and 0.97, respectively, for all SDoH except housing and medication insecurities. The deep learning and regularized logistic regression algorithms had unsatisfactory performance.
conclusionsThe rule-based algorithm can accurately extract SDoH information in all seven domains of SDoH except housing and medication insecurities. Findings from the algorithm can be used by clinicians and social workers to proactively address social needs of patients with ADRD and other vulnerable patient populations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.