5 papers
AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection
Md Mahfuzur Rahman Siddiquee, Fazle Rafsani, Jay Shah +4
Abnormality detection is a crucial yet challenging task in medical image analysis. Distinguishing abnormalities from normal data by learning to reconstruct normal-only data allevia…
Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison
Alejandro Lozano, Keiko Ihara, Ping-Hao Yang +13
Summarizing the latest medical literature to guide clinical decision-making is essential for evidence-based medicine and high-quality patient care. Yet clinicians face increasing c…
PaReGTA: An LLM-based EHR Data Encoding Approach to Capture Temporal Information
Kihyuk Yoon, Lingchao Mao, Catherine Chong +3
Temporal information in structured electronic health records (EHRs) is often lost in sparse one-hot or count-based representations, while sequence models can be costly and data-hun…
MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series
Dohyun Ku, Catherine D. Chong, Visar Berisha +2
Time series analysis has emerged as an important tool for improving patient diagnosis and management in healthcare applications. However, these applications commonly face two criti…
DinoAtten3D: Slice-Level Attention Aggregation of DinoV2 for 3D Brain MRI Anomaly Classification
Fazle Rafsani, Jay Shah, Catherine D. Chong +2
Anomaly detection and classification in medical imaging are critical for early diagnosis but remain challenging due to limited annotated data, class imbalance, and the high cost of…