4 citations · 4 across the 6 of their papers we have counts for
6 papers
Towards causal effect estimation with learned instrument representations
Frances Dean, Jenna Fields, Radhika Bhalerao +2
Instrumental variable (IV) methods mitigate bias from unobserved confounding in observational causal inference but rely on the availability of a valid instrument, which can often b…
Statistical vs. Deep Learning Models for Estimating Substance Overdose Excess Mortality in the US
Sukanya Krishna, Marie-Laure Charpignon, Maimuna Majumder
Substance overdose mortality in the United States claimed over 80,000 lives in 2023, with the COVID-19 pandemic exacerbating existing trends through healthcare disruptions and beha…
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…
Investigating Primary Care Indications to Improve Electronic Health Record in Dementia Target Trial Emulation
Max Sunog, Colin Magdamo, Marie-Laure Charpignon +1
Missing data, inaccuracies in medication lists, and recording delays in electronic health records (EHR) are major limitations for target trial emulation (TTE), the process by which…
What we should learn from pandemic publishing
Satyaki Sikdar, Sara Venturini, Marie-Laure Charpignon +5
Authors of COVID-19 papers produced during the pandemic were overwhelmingly not subject matter experts. Such a massive inflow of scholars from different expertise areas is both an…
Study of the effectiveness of incentive measures on Covid-19 vaccination in the United States of America
Théodore De Pomereu, Antoine Lopes Ferreira, Lucas Leforestier +3
With COVID-19 having emerged as the most widespread human pandemic disease in a century, the need to control its spread to avoid massive loss of life became more than necessary, an…