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Electronic Health Records [PDF]
Forces are aligning to shift American health care into the Information Age: an age which financial institutions, airlines, supermarkets and most manufacturing industries have already entered. The shift, which these institutions have already experienced, will facilitate the establishment and widespread use of standardized databases in health care.
Edward P. Ambinder
+6 more sources
Using Blockchain for Electronic Health Records
Blockchain have been an interesting research area for a long time and the benefits it provides have been used by a number of various industries. Similarly, the healthcare sector stands to benefit immensely from the blockchain technology due to security ...
Ayesha Shahnaz+2 more
doaj +2 more sources
Flexible imputation toolkit for electronic health records [PDF]
Missing data in electronic health records (EHRs) poses a significant challenge for analysis. This study introduces Pympute, a comprehensive Python package designed for efficient and robust missing value imputation for EHRs.
Alireza Vafaei Sadr+7 more
doaj +2 more sources
Large language models to identify social determinants of health in electronic health records [PDF]
Social determinants of health (SDoH) play a critical role in patient outcomes, yet their documentation is often missing or incomplete in the structured data of electronic health records (EHRs).
Marco Guevara+13 more
semanticscholar +1 more source
A large language model for electronic health records [PDF]
There is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powered by pretrained language models is the key technology for medical AI ...
Xi Yang+18 more
semanticscholar +1 more source
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 care and hospital operations.
Michael Wornow+8 more
semanticscholar +1 more source
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction [PDF]
Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver impressive performance in many clinical tasks. Large training cohorts, however, are often required by these models to achieve high accuracy, hindering the adoption ...
L. Rasmy+4 more
semanticscholar +1 more source
Introduction: Electronic medical records (EMRs) are computerized medical information systems that collect, store, and display patient information and essential for the achievement of primary health-care goals.
Ravi Barigela+2 more
doaj +1 more source
This study aims to explore machine learning (ML) methods for early prediction of Alzheimer's disease (AD) and related dementias (ADRD) using the real‐world electronic health records (EHRs).
Qian Li+16 more
semanticscholar +1 more source
Artificial intelligence-based methods for fusion of electronic health records and imaging data [PDF]
Healthcare data are inherently multimodal, including electronic health records (EHR), medical images, and multi-omics data. Combining these multimodal data sources contributes to a better understanding of human health and provides optimal personalized ...
Farida Mohsen+3 more
semanticscholar +1 more source