Search Results for author: Steven Horng

Found 15 papers, 4 papers with code

Bidirectional Captioning for Clinically Accurate and Interpretable Models

no code implementations30 Oct 2023 Keegan Quigley, Miriam Cha, Josh Barua, Geeticka Chauhan, Seth Berkowitz, Steven Horng, Polina Golland

Vision-language pretraining has been shown to produce high-quality visual encoders which transfer efficiently to downstream computer vision tasks.

Contrastive Learning Image Captioning

Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes

no code implementations9 Aug 2023 Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David Karger, David Sontag

The large amount of time clinicians spend sifting through patient notes and documenting in electronic health records (EHRs) is a leading cause of clinician burnout.

Information Retrieval Retrieval

Sample-Specific Debiasing for Better Image-Text Models

no code implementations25 Apr 2023 Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells, Seth Berkowitz, Steven Horng, Polina Golland

Self-supervised representation learning on image-text data facilitates crucial medical applications, such as image classification, visual grounding, and cross-modal retrieval.

Contrastive Learning Cross-Modal Retrieval +4

Using Multiple Instance Learning to Build Multimodal Representations

no code implementations11 Dec 2022 Peiqi Wang, William M. Wells, Seth Berkowitz, Steven Horng, Polina Golland

Image-text multimodal representation learning aligns data across modalities and enables important medical applications, e. g., image classification, visual grounding, and cross-modal retrieval.

Contrastive Learning Cross-Modal Retrieval +5

RadTex: Learning Efficient Radiograph Representations from Text Reports

no code implementations5 Aug 2022 Keegan Quigley, Miriam Cha, Ruizhi Liao, Geeticka Chauhan, Steven Horng, Seth Berkowitz, Polina Golland

In this paper, we build a data-efficient learning framework that utilizes radiology reports to improve medical image classification performance with limited labeled data (fewer than 1000 examples).

Domain Adaptation Image Captioning +2

Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment

1 code implementation22 Aug 2020 Geeticka Chauhan, Ruizhi Liao, William Wells, Jacob Andreas, Xin Wang, Seth Berkowitz, Steven Horng, Peter Szolovits, Polina Golland

To take advantage of the rich information present in the radiology reports, we develop a neural network model that is trained on both images and free-text to assess pulmonary edema severity from chest radiographs at inference time.

Image Classification Representation Learning

Deep Learning to Quantify Pulmonary Edema in Chest Radiographs

1 code implementation13 Aug 2020 Steven Horng, Ruizhi Liao, Xin Wang, Sandeep Dalal, Polina Golland, Seth J. Berkowitz

Results: The area under the receiver operating characteristic curve (AUC) for differentiating alveolar edema from no edema was 0. 99 for the semi-supervised model and 0. 87 for the pre-trained models.

Fast, Structured Clinical Documentation via Contextual Autocomplete

1 code implementation29 Jul 2020 Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag

We present a system that uses a learned autocompletion mechanism to facilitate rapid creation of semi-structured clinical documentation.

Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph

no code implementations2 Oct 2019 Irene Y. Chen, Monica Agrawal, Steven Horng, David Sontag

Increasingly large electronic health records (EHRs) provide an opportunity to algorithmically learn medical knowledge.

Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images

no code implementations27 Feb 2019 Ruizhi Liao, Jonathan Rubin, Grace Lam, Seth Berkowitz, Sandeep Dalal, William Wells, Steven Horng, Polina Golland

We propose and demonstrate machine learning algorithms to assess the severity of pulmonary edema in chest x-ray images of congestive heart failure patients.

BIG-bench Machine Learning

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

no code implementations21 Jan 2019 Alistair E. W. Johnson, Tom J. Pollard, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G. Mark, Seth J. Berkowitz, Steven Horng

Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation.

Clinical Tagging with Joint Probabilistic Models

no code implementations2 Aug 2016 Yoni Halpern, Steven Horng, David Sontag

We describe a method for parameter estimation in bipartite probabilistic graphical models for joint prediction of clinical conditions from the electronic medical record.

Anchored Discrete Factor Analysis

no code implementations10 Nov 2015 Yoni Halpern, Steven Horng, David Sontag

We present a semi-supervised learning algorithm for learning discrete factor analysis models with arbitrary structure on the latent variables.

Medical Diagnosis TAG

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