4 papers
Missingness as Signal: Channel-Independent Spectrogram Learning for Clinical Time Series Prediction
Soyeon Park, Charmgil Hong
Clinical time series prediction in intensive care units remains challenging due to heterogeneous physiological variables and informative missingness. The presence or absence of a m…
Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations
Soyeon Park, Doohee Chung, Charmgil Hong
Forecasting multivariate time series remains challenging due to complex cross-variable dependencies and the presence of heterogeneous external influences. This paper presents Spect…
Retrieval-Augmented VLMs for Multimodal Melanoma Diagnosis
Jihyun Moon, Charmgil Hong
Accurate and early diagnosis of malignant melanoma is critical for improving patient outcomes. While convolutional neural networks (CNNs) have shown promise in dermoscopic image an…
Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays
Harim Kim, Yuhan Wang, Minkyu Ahn +3
Unsupervised anomaly detection (UAD) in medical imaging is crucial for identifying pathological abnormalities without requiring extensive labeled data. However, existing diffusion-…