Construction of cardiovascular information extraction corpus based on electronic medical records

Review Biology

Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review

Elias Hossain et al.

Summary: This study comprehensively investigates the applications of machine learning, deep learning, and natural language processing techniques in electronic health records. It identifies the limitations, such as lack of annotated data and automated tools, that hinder the full utilization of these techniques. The study also highlights common use cases and methods, as well as the need to address model assessment and data imbalance issues.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

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Article Biology

Evaluation of machine learning strategies for imaging confirmed prostate cancer recurrence prediction on electronic health records

Jacqueline Michelle Beinecke et al.

Summary: This study aims to improve the prediction of imaging confirmed prostate cancer recurrence (IPCR) by employing modern multivariate machine learning methods on electronic health records (EHR) of prostate cancer patients. The research found that features such as PSA, hormonal therapy, etc. are important for IPCR prediction.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

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Article Biology

How to ensure the confidentiality of electronic medical records on the cloud: A technical perspective

Zongda Wu et al.

Summary: This paper proposes an effective confidential management solution for electronic medical records on the cloud, using a trusted local server to ensure the confidentiality, accuracy, and efficiency of the records.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

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Article Mathematical & Computational Biology

Application of cascade binary pointer tagging in joint entity and relation extraction of Chinese medical text

Hongyang Chang et al.

Summary: This paper investigates the effectiveness of two models based on CBPTN in the joint entity and relation extraction of Chinese medical texts. The experimental results on two Chinese medical datasets demonstrate the effectiveness of the proposed models. They achieved improved F1 values compared to the baseline model CasREL.

MATHEMATICAL BIOSCIENCES AND ENGINEERING (2022)

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Article Computer Science, Interdisciplinary Applications