Results 21 to 30 of about 1,719,331 (373)

Early prediction of Alzheimer’s disease and related dementias using real-world electronic health records

Alzheimer's & Dementia, 2023
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, Xi Yang, Jie Xu, Yi Guo, Xing He, Hui Hu, Tianchen Lyu, D. Marra, Amber H. Miller, Glenn E. Smith, S. DeKosky, R. Boyce, K. Schliep, E. Shenkman, D. Maraganore, Yonghui Wu, Jiang Bian   +16 more
semanticscholar   +1 more source

BEHRT: Transformer for Electronic Health Records [PDF]

Scientific Reports, 2019
Today, despite decades of developments in medicine and the growing interest in precision healthcare, vast majority of diagnoses happen once patients begin to show noticeable signs of illness.
Yikuan Li, Shishir Rao, J. R. A. Solares, A. Hassaine, R. Ramakrishnan, D. Canoy, Yajie Zhu, K. Rahimi, G. Salimi-Khorshidi   +8 more
semanticscholar   +1 more source

Integration of Healthcare 4.0 and blockchain into secure cloud-based electronic health records systems

Applied Nanoscience, 2022
Since the last decade, cloud-based electronic health records (EHRs) have gained significant attention to enable remote patient monitoring. The recent development of Healthcare 4.0 using the Internet of Things (IoT) components and cloud computing to ...
Hemant B. Mahajan, Ameer Sardar Kwekha Rashid, A. Junnarkar, Nilesh J. Uke, Sarita D. Deshpande, P. R. Futane, Ahmed Alkhayyat, Bilal S. A. Alhayani   +7 more
semanticscholar   +1 more source

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines

npj Digital Medicine, 2020
Advancements in deep learning techniques carry the potential to make significant contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis, prognosis, and treatment decisions.
Shih-Cheng Huang, A. Pareek, S. Seyyedi, I. Banerjee, M. Lungren   +4 more
semanticscholar   +1 more source

Missing Value Imputation Methods for Electronic Health Records

IEEE Access, 2023
Electronic health records (EHR) are patient-level information, e.g., laboratory tests and questionnaires, stored in electronic format. Compared to physical records, the EHR alternative allows patients to access their data easily and helps staff with ...
Konstantinos Psychogyios, Loukas Ilias, Christos Ntanos, D. Askounis   +3 more
semanticscholar   +1 more source

Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records [PDF]

IEEE journal of biomedical and health informatics, 2021
Electronic health records (EHR) represent a holistic overview of patients’ trajectories. Their increasing availability has fueled new hopes to leverage them and develop accurate risk prediction models for a wide range of diseases.
Yikuan Li, M. Mamouei, G. Salimi-Khorshidi, Shishir Rao, A. Hassaine, D. Canoy, Thomas Lukasiewicz, K. Rahimi   +7 more
semanticscholar   +1 more source

OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.

medRxiv, 2020
Background Establishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data.
The OpenSAFELY Collaborative, E. Williamson, A. Walker, K. Bhaskaran, S. Bacon, C. Bates, C. Morton, H. Curtis, A. Mehrkar, D. Evans, P. Inglesby, J. Cockburn, H. Mcdonald, B. Mackenna, L. Tomlinson, I. Douglas, C. Rentsch, R. Mathur, A. Wong, R. Grieve, D. Harrison, H. Forbes, Anna Schultze, R. Croker, J. Parry, F. Hester, S. Harper, R. Perera, S. Evans, L. Smeeth, B. Goldacre   +30 more
semanticscholar   +1 more source

Hybrid electronic health records [PDF]

, 2011
The research related with digital health records has been a hot topic since the last two decades, producing diverse results, particularly in two main types – Electronic Health Records and Personal Health Records.
Costa, Carlos Manuel Azevedo, Lopes, Rui Pedro, Oliveira, José Luís, Pedrosa, Tiago, Santos, João C.   +4 more
core   +1 more source

Predicting diabetes-related hospitalizations based on electronic health records [PDF]

, 2019
OBJECTIVE: To derive a predictive model to identify patients likely to be hospitalized during the following year due to complications attributed to Type II diabetes. METHODS: A variety of supervised machine learning classification methods were tested and
Brisimi, Theodora S., Dai, Wuyang, Paschalidis, Ioannis Ch., Wang, Taiyao, Xu, Tingting   +4 more
core   +1 more source

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

Scientific Reports, 2016
Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs ...
Riccardo Miotto, Li Li, B. Kidd, J. Dudley   +3 more
semanticscholar   +1 more source