10 citations · 35 across the 13 of their papers we have counts for
13 papers
Incorporating Human Explanations for Robust Hate Speech Detection
Jennifer L. Chen, Faisal Ladhak, Daniel Li +1
Given the black-box nature and complexity of large transformer language models (LM), concerns about generalizability and robustness present ethical implications for domains such as…
Probabilistic Shapley Value Modeling and Inference
Mert Ketenci, Iñigo Urteaga, Victor Alfonso Rodriguez +2
We propose probabilistic Shapley inference (PSI), a novel probabilistic framework to model and infer sufficient statistics of feature attributions in flexible predictive models, vi…
SPEER: Sentence-Level Planning of Long Clinical Summaries via Embedded Entity Retrieval
Griffin Adams, Jason Zucker, Noémie Elhadad
Clinician must write a lengthy summary each time a patient is discharged from the hospital. This task is time-consuming due to the sheer number of unique clinical concepts covered…
Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
Mert Ketenci, Adler Perotte, Noémie Elhadad +1
We introduce a novel stochastic variational inference method for Gaussian process () regression, by deriving a posterior over a learnable set of coresets: i.e., over…
Assisted Living in the United States: an Open Dataset
Anton Stengel, Jaan Altosaar, Rebecca Dittrich +1
An assisted living facility (ALF) is a place where someone can live, have access to social supports such as transportation, and receive assistance with the activities of daily livi…
Causal Fairness Assessment of Treatment Allocation with Electronic Health Records
Linying Zhang, Lauren R. Richter, Yixin Wang +4
Healthcare continues to grapple with the persistent issue of treatment disparities, sparking concerns regarding the equitable allocation of treatments in clinical practice. While v…
Assessing Phenotype Definitions for Algorithmic Fairness
Tony Y. Sun, Shreyas Bhave, Jaan Altosaar +1
Disease identification is a core, routine activity in observational health research. Cohorts impact downstream analyses, such as how a condition is characterized, how patient risk…
Exploring Gender Disparities in Time to Diagnosis
Tony Y. Sun, Oliver J. Bear Don't Walk, Jennifer L. Chen +2
Sex and gender-based healthcare disparities contribute to differences in health outcomes. We focus on time to diagnosis (TTD) by conducting two large-scale, complementary analyses…
Reduced model for female endocrine dynamics: Validation and functional variations
E. J. Graham, N. Elhadad, D. Albers
A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnorm…
Towards Patient Record Summarization Through Joint Phenotype Learning in HIV Patients
Gal Levy-Fix, Jason Zucker, Konstantin Stojanovic +1
Identifying a patient's key problems over time is a common task for providers at the point care, yet a complex and time-consuming activity given current electric health records. To…
Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data
Kathy Li, Iñigo Urteaga, Chris H. Wiggins +4
The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual…
Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy +2
We present an end-to-end statistical framework for personalized, accurate, and minimally invasive modeling of female reproductive hormonal patterns. Reconstructing and forecasting…
Machine Learning and Visualization in Clinical Decision Support: Current State and Future Directions
Gal Levy-Fix, Gilad J. Kuperman, Noémie Elhadad
Deep learning, an area of machine learning, is set to revolutionize patient care. But it is not yet part of standard of care, especially when it comes to individual patient care. I…