Search Results for author: Adler Perotte

Found 9 papers, 1 papers with code

Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling

no code implementations3 Nov 2023 Mert Ketenci, Shreyas Bhave, Noémie Elhadad, Adler Perotte

We propose a survival analysis approach which eliminates the need to tune hyperparameters such as mixture assignments and bin sizes, reducing the burden on practitioners.

Survival Analysis

A Coreset-based, Tempered Variational Posterior for Accurate and Scalable Stochastic Gaussian Process Inference

no code implementations2 Nov 2023 Mert Ketenci, Adler Perotte, Noémie Elhadad, Iñigo Urteaga

We present a novel stochastic variational Gaussian process ($\mathcal{GP}$) inference method, based on a posterior over a learnable set of weighted pseudo input-output points (coresets).

Stochastic Optimization

CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks

no code implementations10 Nov 2021 Chao Pang, Xinzhuo Jiang, Krishna S Kalluri, Matthew Spotnitz, Ruijun Chen, Adler Perotte, Karthik Natarajan

CEHR-BERT also demonstrated strong transfer learning capability, as our model trained on only 5% of data outperformed comparison models trained on the entire data set.

Disease Prediction Transfer Learning

Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells

1 code implementation29 Sep 2020 Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte, Noémie Elhadad

We introduce Latent Meaning Cells, a deep latent variable model which learns contextualized representations of words by combining local lexical context and metadata.

Representation Learning

Phenotype Inference with Semi-Supervised Mixed Membership Models

no code implementations7 Dec 2018 Victor Rodriguez, Adler Perotte

Disease phenotyping algorithms process observational clinical data to identify patients with specific diseases.

Multiple Causal Inference with Latent Confounding

no code implementations21 May 2018 Rajesh Ranganath, Adler Perotte

Together, these assumptions lead to a confounder estimator regularized by mutual information.

Causal Inference

Deep Survival Analysis

no code implementations6 Aug 2016 Rajesh Ranganath, Adler Perotte, Noémie Elhadad, David Blei

The electronic health record (EHR) provides an unprecedented opportunity to build actionable tools to support physicians at the point of care.

Survival Analysis

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