[HTML][HTML] Develo** an LSTM model to identify surgical site infections using electronic healthcare records

AC Kiser, K Eilbeck, BT Bucher - AMIA Summits on Translational …, 2023 - ncbi.nlm.nih.gov
Recently, hospitals and healthcare providers have made efforts to reduce surgical site
infections as they are a major cause of surgical complications, a prominent reason for …

Identifying diabetes related-complications in a real-world free-text electronic medical records in Hebrew using natural language processing techniques

M Saban, M Lutski, I Zucker, M Uziel… - Journal of Diabetes …, 2024 - journals.sagepub.com
Background: Studies have demonstrated that 50% to 80% of patients do not receive an
International Classification of Diseases (ICD) code assigned to their medical encounter or …

NER sequence embedding of unified medical corpora to incorporate semantic intelligence in big data healthcare diagnostics

S Shafqat, Z Anwar, Q Javaid, HF Ahmad - 2024 - researchsquare.com
Clinical diagnosis is a challenging task for which high expertise is required at the doctors'
end. It is recognized that technology integration with the clinical domain would facilitate the …

Generating longitudinal synthetic ehr data with recurrent autoencoders and generative adversarial networks

S Sun, F Wang, S Rashidian, T Kurc… - … , and Analytics for …, 2021 - Springer
Synthetic electronic health records (EHR) can facilitate effective use of clinical data in
software development, medical education, and medical research without the concerns of …

Generating Longitudinal Synthetic EHR Data with Recurrent Autoencoders and Generative Adversarial Networks

K Abell-Hart, J Hajagos, W Zhu, M Saltz… - … , Polystores, and Analytics …, 2021 - Springer
Synthetic electronic health records (EHR) can facilitate effective use of clinical data in
software development, medical education, and medical research without the concerns of …