Search Results for author: Prithwish Chakraborty

Found 17 papers, 3 papers with code

Improving Primary Healthcare Workflow Using Extreme Summarization of Scientific Literature Based on Generative AI

no code implementations24 Jul 2023 Gregor Stiglic, Leon Kopitar, Lucija Gosak, Primoz Kocbek, Zhe He, Prithwish Chakraborty, Pablo Meyer, Jiang Bian

The time needed to answer questions related to the content of abstracts was significantly lower in groups two and three compared to the first group using full abstracts.

Extreme Summarization

Distillation to Enhance the Portability of Risk Models Across Institutions with Large Patient Claims Database

no code implementations6 Jul 2022 Steve Nyemba, Chao Yan, Ziqi Zhang, Amol Rajmane, Pablo Meyer, Prithwish Chakraborty, Bradley Malin

We further show that the transfer learning approach based on the BAN produces models that are better than those trained on just a single institution's data.

Readmission Prediction Transfer Learning

Simpler Calibration for Survival Analysis

no code implementations29 Sep 2021 Hiroki Yanagisawa, Toshiya Iwamori, Akira Koseki, Michiharu Kudo, Mohamed Ghalwash, Prithwish Chakraborty

Therefore, X-CAL has recently been proposed for the calibration, which is supposed to be used as a regularization term in the loss function of a neural network.

regression Survival Analysis

Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case

no code implementations6 Jul 2021 Shruthi Chari, Prithwish Chakraborty, Mohamed Ghalwash, Oshani Seneviratne, Elif K. Eyigoz, Daniel M. Gruen, Fernando Suarez Saiz, Ching-Hua Chen, Pablo Meyer Rojas, Deborah L. McGuinness

To enable the adoption of the ever improving AI risk prediction models in practice, we have begun to explore techniques to contextualize such models along three dimensions of interest: the patients' clinical state, AI predictions about their risk of complications, and algorithmic explanations supporting the predictions.

Disease Progression Modeling Workbench 360

no code implementations24 Jun 2021 Parthasarathy Suryanarayanan, Prithwish Chakraborty, Piyush Madan, Kibichii Bore, William Ogallo, Rachita Chandra, Mohamed Ghalwash, Italo Buleje, Sekou Remy, Shilpa Mahatma, Pablo Meyer, Jianying Hu

In this work we introduce Disease Progression Modeling workbench 360 (DPM360) opensource clinical informatics framework for collaborative research and delivery of healthcare AI.

BIG-bench Machine Learning

Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare

1 code implementation16 May 2021 Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning

Accurate and explainable health event predictions are becoming crucial for healthcare providers to develop care plans for patients.

Graph Learning

Phenotypical Ontology Driven Framework for Multi-Task Learning

no code implementations4 Sep 2020 Mohamed Ghalwash, Zijun Yao, Prithwish Chakraborty, James Codella, Daby Sow

Despite the large number of patients in Electronic Health Records (EHRs), the subset of usable data for modeling outcomes of specific phenotypes are often imbalanced and of modest size.

Multi-Task Learning

A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records

no code implementations24 Jul 2020 Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty, Bibo Hao, Italo Buleje, Piyush Madan, James Codella, Antonio Foncubierta, Divya Pathak, Sarah Miller, Amol Rajmane, Shannon Harrer, Gigi Yuan-Reed, Daby Sow

Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient outcomes.

Fairness Management

Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records

no code implementations15 Nov 2019 Prithwish Chakraborty, Fei Wang, Jianying Hu, Daby Sow

While networks with explicit memory have been proposed recently, the discontinuities imposed by the discrete operations make such networks harder to train and require more supervision.

A Novel Data-Driven Framework for Risk Characterization and Prediction from Electronic Medical Records: A Case Study of Renal Failure

no code implementations29 Nov 2017 Prithwish Chakraborty, Vishrawas Gopalakrishnan, Sharon M. H. Alford, Faisal Farooq

To validate the identified factors, we use a specialized generalized linear model (GLM) to predict the probability of renal failure for individual patients within a specified time window.

Hierarchical Quickest Change Detection via Surrogates

no code implementations31 Mar 2016 Prithwish Chakraborty, Sathappan Muthiah, Ravi Tandon, Naren Ramakrishnan

We propose hierarchical quickest change detection (HQCD), a framework that formalizes the process of incorporating additional correlated sources for early changepoint detection.

Change Detection Time Series +1

Characterizing Diseases from Unstructured Text: A Vocabulary Driven Word2vec Approach

1 code implementation1 Mar 2016 Saurav Ghosh, Prithwish Chakraborty, Emily Cohn, John S. Brownstein, Naren Ramakrishnan

Traditional disease surveillance can be augmented with a wide variety of real-time sources such as, news and social media.

Word Embeddings

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