The shaky foundations of large language models and foundation models for electronic health records
The success of foundation models such as ChatGPT and AlphaFold has spurred significant
interest in building similar models for electronic medical records (EMRs) to improve patient …
interest in building similar models for electronic medical records (EMRs) to improve patient …
Pre-training in medical data: A survey
Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …
part of a clinical trial program. There are many categories of such data, such as clinical …
Ehrshot: An ehr benchmark for few-shot evaluation of foundation models
M Wornow, R Thapa, E Steinberg… - Advances in Neural …, 2023 - proceedings.neurips.cc
While the general machine learning (ML) community has benefited from public datasets,
tasks, and models, the progress of ML in healthcare has been hampered by a lack of such …
tasks, and models, the progress of ML in healthcare has been hampered by a lack of such …
Multimodal clinical benchmark for emergency care (mc-bec): A comprehensive benchmark for evaluating foundation models in emergency medicine
Abstract We propose the Multimodal Clinical Benchmark for Emergency Care (MC-BEC), a
comprehensive benchmark for evaluating foundation models in Emergency Medicine using …
comprehensive benchmark for evaluating foundation models in Emergency Medicine using …
Genhpf: General healthcare predictive framework for multi-task multi-source learning
Despite the remarkable progress in the development of predictive models for healthcare,
applying these algorithms on a large scale has been challenging. Algorithms trained on a …
applying these algorithms on a large scale has been challenging. Algorithms trained on a …
A multi-center study on the adaptability of a shared foundation model for electronic health records
Foundation models are transforming artificial intelligence (AI) in healthcare by providing
modular components adaptable for various downstream tasks, making AI development more …
modular components adaptable for various downstream tasks, making AI development more …
Unihpf: Universal healthcare predictive framework with zero domain knowledge
Despite the abundance of Electronic Healthcare Records (EHR), its heterogeneity restricts
the utilization of medical data in building predictive models. To address this challenge, we …
the utilization of medical data in building predictive models. To address this challenge, we …
Comparing neural language models for medical concept representation and patient trajectory prediction
Effective representation of medical concepts is crucial for secondary analyses of electronic
health records. Neural language models have shown promise in automatically deriving …
health records. Neural language models have shown promise in automatically deriving …
sEHR-CE: Language modelling of structured EHR data for efficient and generalizable patient cohort expansion
A Munoz-Farre, H Rose, SA Cakiroglu - arXiv preprint arXiv:2211.17121, 2022 - arxiv.org
Electronic health records (EHR) offer unprecedented opportunities for in-depth clinical
phenotyping and prediction of clinical outcomes. Combining multiple data sources is crucial …
phenotyping and prediction of clinical outcomes. Combining multiple data sources is crucial …
Universal EHR federated learning framework
Federated learning (FL) is the most practical multi-source learning method for electronic
healthcare records (EHR). Despite its guarantee of privacy protection, the wide application …
healthcare records (EHR). Despite its guarantee of privacy protection, the wide application …