3 citations · 8 across the 14 of their papers we have counts for
6 papers · 1 filter
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…
Deep sequence models tend to memorize geometrically; it is unclear why
Shahriar Noroozizadeh, Vaishnavh Nagarajan, Elan Rosenfeld +1
Deep sequence models are said to store atomic facts predominantly in the form of associative memory: a brute-force lookup of co-occurring entities. We identify a dramatically diffe…
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…
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…