Search Results for author: Hyewon Jeong

Found 10 papers, 6 papers with code

Adaptive Collaboration Strategy for LLMs in Medical Decision Making

no code implementations22 Apr 2024 Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik Siu Chan, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, Hae Won Park

Our novel framework, Medical Decision-making Agents (MDAgents) aims to address this gap by automatically assigning the effective collaboration structure for LLMs.

Event-Based Contrastive Learning for Medical Time Series

1 code implementation16 Dec 2023 Hyewon Jeong, Nassim Oufattole, Matthew McDermott, Aparna Balagopalan, Bryan Jangeesingh, Marzyeh Ghassemi, Collin Stultz

In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event.

Contrastive Learning Decision Making +2

Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals

1 code implementation9 Aug 2023 Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi

Additionally, the supervised DML model that uses ECGs with access to 8, 172 mPCWP labels demonstrated significantly better performance on the mPCWP regression task compared to the supervised baseline.

Metric Learning

Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting

1 code implementation21 Jan 2022 Kwanhyung Lee, Hyewon Jeong, Seyun Kim, Donghwa Yang, Hoon-Chul Kang, Edward Choi

Electroencephalogram (EEG) is an important diagnostic test that physicians use to record brain activity and detect seizures by monitoring the signals.

EEG Seizure Detection

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

2 code implementations23 Jun 2020 A. Tuan Nguyen, Hyewon Jeong, Eunho Yang, Sung Ju Hwang

Existing asymmetric multi-task learning methods tackle this negative transfer problem by performing knowledge transfer from tasks with low loss to tasks with high loss.

Knowledge Graphs Multi-Task Learning +2

Temporal Probabilistic Asymmetric Multi-task Learning

no code implementations25 Sep 2019 Nguyen Anh Tuan, Hyewon Jeong, Eunho Yang, Sungju Hwang

To capture such dynamically changing asymmetric relationships between tasks and long-range temporal dependencies in time-series data, we propose a novel temporal asymmetric multi-task learning model, which learns to combine features from other tasks at diverse timesteps for the prediction of each task.

Multi-Task Learning Time Series +1

Cannot find the paper you are looking for? You can Submit a new open access paper.