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08/04/2023
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology
Clinical trial matching is a key process in health delivery and discover...
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07/12/2023
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events
Large language models (LLMs), such as GPT-4, have demonstrated remarkabl...
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06/01/2023
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
Conversational generative AI has demonstrated remarkable promise for emp...
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05/27/2023
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification
Pre-trained transformer models have demonstrated success across many nat...
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05/12/2023
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization
Summarization models often generate text that is poorly calibrated to qu...
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03/02/2023
Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing
Contrastive pretraining on parallel image-text data has attained great s...
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12/21/2022
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction
Relation extraction (RE), which has relied on structurally annotated cor...
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04/21/2022
Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing
Multi-modal data abounds in biomedicine, such as radiology images and re...
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03/20/2022
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision
Objective: The majority of detailed patient information in real-world da...
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12/15/2021
Knowledge-Rich Self-Supervised Entity Linking
Entity linking faces significant challenges, such as prolific variations...
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12/15/2021
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing
Motivation: A perennial challenge for biomedical researchers and clinica...
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09/11/2021
Modular Self-Supervision for Document-Level Relation Extraction
Extracting relations across large text spans has been relatively underex...
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06/25/2021
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature
Information overload is a prevalent challenge in many high-value domains...
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07/31/2020
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
Pretraining large neural language models, such as BERT, has led to impre...
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02/05/2020
ML4H Abstract Track 2019
A collection of the accepted abstracts for the Machine Learning for Heal...
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08/02/2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
When training clinical prediction models from electronic health records ...
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07/19/2019
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Robust machine learning relies on access to data that can be used with s...
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04/06/2019
Publicly Available Clinical BERT Embeddings
Contextual word embedding models such as ELMo (Peters et al., 2018) and ...
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12/06/2018
Generalizability of predictive models for intensive care unit patients
A large volume of research has considered the creation of predictive mod...
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11/30/2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation
Machine learning for healthcare often trains models on de-identified dat...
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11/17/2018
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
This volume represents the accepted submissions from the Machine Learnin...
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06/13/2018
Natural Language Processing for EHR-Based Computational Phenotyping
This article reviews recent advances in applying natural language proces...
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06/01/2018
Visualizing Patient Timelines in the Intensive Care Unit
Electronic Health Records (EHRs) contain a large volume of heterogeneous...
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06/01/2018
Opportunities in Machine Learning for Healthcare
Healthcare is a natural arena for the application of machine learning, e...
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03/07/2018
Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes
Clinical notes often describe the most important aspects of a patient's ...
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03/06/2018
