Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records

1 code implementation • 6 Mar 2024 • Suhan Cui, Prasenjit Mitra

To reduce human intervention and improve the framework design, we propose an automated approach named AutoDP, which can search for the optimal configuration of task grouping and architectures simultaneously.

Disease Prediction Multi-Task Learning

Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions

1 code implementation • 20 Jan 2024 • Suhan Cui, Jiaqi Wang, Yuan Zhong, Han Liu, Ting Wang, Fenglong Ma

The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improving healthcare services through deep learning techniques.

Neural Architecture Search

Hierarchical Pretraining on Multimodal Electronic Health Records

1 code implementation • 11 Oct 2023 • Xiaochen Wang, Junyu Luo, Jiaqi Wang, Ziyi Yin, Suhan Cui, Yuan Zhong, Yaqing Wang, Fenglong Ma

Pretraining has proven to be a powerful technique in natural language processing (NLP), exhibiting remarkable success in various NLP downstream tasks.

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation

no code implementations • 4 Oct 2023 • Yuan Zhong, Suhan Cui, Jiaqi Wang, Xiaochen Wang, Ziyi Yin, Yaqing Wang, Houping Xiao, Mengdi Huai, Ting Wang, Fenglong Ma

Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in the future using their historical Electronic Health Records (EHR).

Data Augmentation