Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review
Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
insights from Electronic Health Records (EHRs). However, the lack of annotated data …
Deid-gpt: Zero-shot medical text de-identification by gpt-4
The digitization of healthcare has facilitated the sharing and re-using of medical data but has
also raised concerns about confidentiality and privacy. HIPAA (Health Insurance Portability …
also raised concerns about confidentiality and privacy. HIPAA (Health Insurance Portability …
A survey of deep learning for electronic health records
Medical data is an important part of modern medicine. However, with the rapid increase in
the amount of data, it has become hard to use this data effectively. The development of …
the amount of data, it has become hard to use this data effectively. The development of …
[HTML][HTML] Smartphone apps for diabetes medication adherence: systematic review
Background: Diabetes is one of the leading noncommunicable chronic diseases globally. In
people with diabetes, blood glucose levels need to be monitored regularly and managed …
people with diabetes, blood glucose levels need to be monitored regularly and managed …
[HTML][HTML] AGORA: An intelligent system for the anonymization, information extraction and automatic mapping of sensitive documents
R Juez-Hernandez, L Quijano-Sánchez… - Applied Soft …, 2023 - Elsevier
Public institutions, such as law enforcement agencies or health centers, have a vast volume
of unstructured text documents, eg police reports. Currently, before this data can be shared …
of unstructured text documents, eg police reports. Currently, before this data can be shared …
[HTML][HTML] Opendeid pipeline for unstructured electronic health record text notes based on rules and transformers: Deidentification algorithm development and validation …
Background Electronic health records (EHRs) in unstructured formats are valuable sources
of information for research in both the clinical and biomedical domains. However, before …
of information for research in both the clinical and biomedical domains. However, before …
Surviving ChatGPT in healthcare
At the dawn of of Artificial General Intelligence (AGI), the emergence of large language
models such as ChatGPT show promise in revolutionizing healthcare by improving patient …
models such as ChatGPT show promise in revolutionizing healthcare by improving patient …
Utilizing ChatGPT to enhance clinical trial enrollment
Clinical trials are a critical component of evaluating the effectiveness of new medical
interventions and driving advancements in medical research. Therefore, timely enrollment of …
interventions and driving advancements in medical research. Therefore, timely enrollment of …
De-identification of clinical free text using natural language processing: A systematic review of current approaches
Abstract Background Electronic health records (EHRs) are a valuable resource for data-
driven medical research. However, the presence of protected health information (PHI) …
driven medical research. However, the presence of protected health information (PHI) …
Cross-language transfer of high-quality annotations: Combining neural machine translation with cross-linguistic span alignment to apply NER to clinical texts in a low …
H Schäfer, A Idrissi-Yaghir, P Horn… - Proceedings of the 4th …, 2022 - aclanthology.org
In this work, cross-linguistic span prediction based on contextualized word embedding
models is used together with neural machine translation (NMT) to transfer and apply the …
models is used together with neural machine translation (NMT) to transfer and apply the …