Jason Alan Fries

Orcid: 0000-0001-9316-5768

Affiliations:
  • Stanford University


According to our database1, Jason Alan Fries authored at least 39 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare.
BMC Medical Informatics Decis. Mak., December, 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.
CoRR, 2024


2023
Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.
J. Am. Medical Informatics Assoc., November, 2023

The shaky foundations of large language models and foundation models for electronic health records.
npj Digit. Medicine, 2023

A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records.
CoRR, 2023

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis.
CoRR, 2023

The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs.
CoRR, 2023

Self-Supervised Time-to-Event Modeling with Structured Medical Records.
CoRR, 2023

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Diagnosis Assignment Using Unstructured Clinical Notes.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing.
CoRR, 2022

Language Models in the Loop: Incorporating Prompting into Weak Supervision.
CoRR, 2022

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts.
CoRR, 2022




2021
Language models are an effective representation learning technique for electronic health record data.
J. Biomed. Informatics, 2021

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR.
CoRR, 2021

Multitask Prompted Training Enables Zero-Shot Task Generalization.
CoRR, 2021

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Appl. Clin. Inform., 2021

2020
Assessing the accuracy of automatic speech recognition for psychotherapy.
npj Digit. Medicine, 2020

Estimating the efficacy of symptom-based screening for COVID-19.
npj Digit. Medicine, 2020

Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening.
J. Am. Medical Informatics Assoc., 2020

Trove: Ontology-driven weak supervision for medical entity classification.
CoRR, 2020

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data.
CoRR, 2020

2019
Medical device surveillance with electronic health records.
npj Digit. Medicine, 2019

The accuracy vs. coverage trade-off in patient-facing diagnosis models.
CoRR, 2019

Multi-Resolution Weak Supervision for Sequential Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.
CoRR, 2018

2017
Snorkel: Rapid Training Data Creation with Weak Supervision.
Proc. VLDB Endow., 2017

SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data.
CoRR, 2017

ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information.
Proceedings of the Machine Learning for Health Care Conference, 2017

Snorkel: A System for Lightweight Extraction.
Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016
Data programming with DDLite: putting humans in a different part of the loop.
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2016

Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction.
Proceedings of the 10th International Workshop on Semantic Evaluation, 2016

2014
Mining the Demographics of Craigslist Casual Sex Ads to Inform Public Health Policy.
Proceedings of the 2014 IEEE International Conference on Healthcare Informatics, 2014

2012
Using Online Classified Ads to Identify the Geographic Footprints of Anonymous, Casual Sex-Seeking Individuals.
Proceedings of the 2012 International Conference on Privacy, 2012


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