2 citations · 3 across the 9 of their papers we have counts for
12 papers
Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case Reports
Jack Cummins, Sayantan Kumar, Ketan Tamirisa +1
Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference annotations and imprecise event…
Hindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment
Misaki Matsuura, Sayantan Kumar, Ojas Kadam +1
Clinical decisions are prospective, but clinical language models are often evaluated on retrospective records that reveal the final diagnosis, treatment response, and outcome. Such…
Anchoring Clinical Events in Time: UID-Preserving Multimodal Reconstruction and Source-Grounded Adjudication
Sayantan Kumar, Nicolas Grimaldi, Jack Cummins +1
Clinical timelines support treatment-window analysis and leakage-free modeling, but discharge summaries often obscure chronology and structured EHR tables describe only part of the…
Text Knows What, Tables Know When: Clinical Timeline Reconstruction via Retrieval-Augmented Multimodal Alignment
Sayantan Kumar, Shahriar Noroozizadeh, Juyong Kim +1
Clinical language models increasingly operate over electronic health records (EHRs), yet patient records are not stored as temporally grounded trajectories. Clinical notes describe…
Temporally Phenotyping GLP-1RA Case Reports with Large Language Models: A Textual Time Series Corpus and Risk Modeling
Sayantan Kumar, Jeremy C. Weiss
Type 2 diabetes case reports describe complex clinical courses, but their timelines are often expressed in language that is difficult to reuse in longitudinal modeling. To address…
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
The Impact of Medication Non-adherence on Adverse Outcomes: Evidence from Schizophrenia Patients via Survival Analysis
Shahriar Noroozizadeh, Pim Welle, Jeremy C. Weiss +1
This study quantifies the association between non-adherence to antipsychotic medications and adverse outcomes in individuals with schizophrenia. We frame the problem using survival…
PMOA-TTS: Introducing the PubMed Open Access Textual Times Series Corpus
Shahriar Noroozizadeh, Sayantan Kumar, George H. Chen +1
Clinical narratives encode temporal dynamics essential for modeling patient trajectories, yet large-scale temporally annotated resources are scarce. We introduce PMOA-TTS, a corpus…
A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reports
Jing Wang, Jeremy C Weiss
Timing of clinical events is central to characterization of patient trajectories, enabling analyses such as process tracing, forecasting, and causal reasoning. However, structured…
Reconstructing Sepsis Trajectories from Clinical Case Reports using LLMs: the Textual Time Series Corpus for Sepsis
Shahriar Noroozizadeh, Jeremy C. Weiss
Clinical case reports and discharge summaries may be the most complete and accurate summarization of patient encounters, yet they are finalized, i.e., timestamped after the encount…
Forecasting Clinical Risk from Textual Time Series: Structuring Narratives for Temporal AI in Healthcare
Shahriar Noroozizadeh, Sayantan Kumar, Jeremy C. Weiss
Clinical case reports encode temporal patient trajectories that are often underexploited by traditional machine learning methods relying on structured data. In this work, we introd…
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression
Shahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen
We consider the problem of predicting how the likelihood of an outcome of interest for a patient changes over time as we observe more of the patient data. To solve this problem, we…