Search Results - "Hahn, Sangchul"

Event Prediction Model Considering Time and Input Error Using Electronic Medical Records in the Intensive Care Unit: Retrospective Study by Sung, MinDong, Hahn, Sangchul, Han, Chang Hoon, Lee, Jung Mo, Lee, Jayoung, Yoo, Jinkyu, Heo, Jay, Kim, Young Sam, Chung, Kyung Soo

“…Background In the era of artificial intelligence, event prediction models are abundant. However, considering the limitation of the electronic medical…”
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Understanding dropout as an optimization trick by Hahn, Sangchul, Choi, Heeyoul

“…As one of standard approaches to train deep neural networks, dropout has been applied to regularize large models to avoid overfitting, and the improvement in…”
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Compact and De-Biased Negative Instance Embedding for Multi-Instance Learning on Whole-Slide Image Classification by Lee, Joohyung, Nam, Heejeong, Lee, Kwanhyung, Hahn, Sangchul

“…Whole-slide image (WSI) classification is a challenging task because 1) patches from WSI lack annotation, and 2) WSI possesses unnecessary variability, e.g.,…”
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Self-Knowledge Distillation in Natural Language Processing by Hahn, Sangchul, Choi, Heeyoul

“…Since deep learning became a key player in natural language processing (NLP), many deep learning models have been showing remarkable performances in a variety…”
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Compact and De-biased Negative Instance Embedding for Multi-Instance Learning on Whole-Slide Image Classification by Lee, Joohyung, Nam, Heejeong, Lee, Kwanhyung, Hahn, Sangchul

“…Whole-slide image (WSI) classification is a challenging task because 1) patches from WSI lack annotation, and 2) WSI possesses unnecessary variability, e.g.,…”
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Disentangling Latent Factors of Variational Auto-Encoder with Whitening by Hahn, Sangchul, Choi, Heeyoul

“…After deep generative models were successfully applied to image generation tasks, learning disentangled latent variables of data has become a crucial part of…”
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Understanding Dropout as an Optimization Trick by Hahn, Sangchul, Choi, Heeyoul

“…As one of standard approaches to train deep neural networks, dropout has been applied to regularize large models to avoid overfitting, and the improvement in…”
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Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention by Lee, Kwanhyung, Lee, Soojeong, Hahn, Sangchul, Hyun, Heejung, Choi, Edward, Ahn, Byungeun, Lee, Joohyung

“…Electronic Health Record (EHR) provides abundant information through various modalities. However, learning multi-modal EHR is currently facing two major…”
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Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-grained Time Resolution by Lee, Kwanhyung, Won, John, Hyun, Heejung, Hahn, Sangchul, Choi, Edward, Lee, Joohyung

“…Accurate time prediction of patients' critical events is crucial in urgent scenarios where timely decision-making is important. Though many studies have…”
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