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20202026
most citedGenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

26 citations · 56 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation

Jungwoo Oh, Hyunseung Chung, Junhee Lee +6

While Multimodal Large Language Models (MLLMs) show promising performance in automated electrocardiogram interpretation, it remains unclear whether they genuinely perform actual st…

cs.LG2025★ 1 cited

LabTOP: A Unified Model for Lab Test Outcome Prediction on Electronic Health Records

Sujeong Im, Jungwoo Oh, Edward Choi

Lab tests are fundamental for diagnosing diseases and monitoring patient conditions. However, frequent testing can be burdensome for patients, and test results may not always be im…

cs.LG2024

Learning under Label Noise through Few-Shot Human-in-the-Loop Refinement

Aaqib Saeed, Dimitris Spathis, Jungwoo Oh +2

Wearable technologies enable continuous monitoring of various health metrics, such as physical activity, heart rate, sleep, and stress levels. A key challenge with wearable data is…

cs.LG2022★ 3 cited

UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge

Kyunghoon Hur, Jungwoo Oh, Junu Kim +6

Despite the abundance of Electronic Healthcare Records (EHR), its heterogeneity restricts the utilization of medical data in building predictive models. To address this challenge,…

cs.LG2022★ 26 cited

GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

Kyunghoon Hur, Jungwoo Oh, Junu Kim +7

Despite the remarkable progress in the development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained on a par…

cs.LG2022★ 4 cited

Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram

Jungwoo Oh, Hyunseung Chung, Joon-myoung Kwon +2

In recent years, self-supervised learning methods have shown significant improvement for pre-training with unlabeled data and have proven helpful for electrocardiogram signals. How…