Hyperparameter Optimization Using Genetic Algorithm for Extracting Social Determinants of Health Text

Navya Martin Kollapally, James Geller

2024

Abstract

Clinical factors account only for a small portion, about 10-30%, of the controllable factors that affect an individual’s health outcomes. The remaining factors include where a person was born and raised, where he/she pursued their education, what their work and family environment is like, etc. These factors are collectively referred to as Social Determinants of Health (SDoH). Our research focuses on extracting sentences from clinical notes, using an SDoH ontology (called SOHO) to provide appropriate concepts. We utilize recent advancements in Deep Learning to optimize the hyperparameters of a Clinical BioBERT model for SDoH text. A genetic algorithm-based hyperparameter tuning regimen improved with principles of simulated annealing was implemented to identify optimal hyperparameter settings. To implement a complete classifier, we pipelined Clinical BioBERT with two subsequent linear layers and two dropout layers. The output predicts whether a text fragment describes an SDoH issue of the patient. The proposed model is compared with an existing optimization framework for both accuracy of identifying optimal parameters and execution time.

Paper Citation

in Harvard Style

Martin Kollapally N. and Geller J. (2024). Hyperparameter Optimization Using Genetic Algorithm for Extracting Social Determinants of Health Text. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 300-307. DOI: 10.5220/0012310300003657

in Bibtex Style

@conference{healthinf24,
author={Navya Martin Kollapally and James Geller},
title={Hyperparameter Optimization Using Genetic Algorithm for Extracting Social Determinants of Health Text},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={300-307},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012310300003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Hyperparameter Optimization Using Genetic Algorithm for Extracting Social Determinants of Health Text
SN - 978-989-758-688-0
AU - Martin Kollapally N.
AU - Geller J.
PY - 2024
SP - 300
EP - 307
DO - 10.5220/0012310300003657
PB - SciTePress