Results 21 to 30 of about 1,599,078 (384)

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

Machine learning model to predict mental health crises from electronic health records

Nature Network Boston, 2022
The timely identification of patients who are at risk of a mental health crisis can lead to improved outcomes and to the mitigation of burdens and costs.
Roger Garriga, Javier Mas, S. Abraha, Jon Nolan, Oliver Harrison, G. Tadros, Aleksandar Matic   +6 more
semanticscholar   +1 more source

The Secondary Use of Electronic Health Records for Data Mining: Data Characteristics and Challenges

ACM Computing Surveys, 2022
The primary objective of implementing Electronic Health Records (EHRs) is to improve the management of patients’ health-related information. However, these records have also been extensively used for the secondary purpose of clinical research and to ...
Tabinda Sarwar, Sattar Seifollahi, Jeffrey A Chan, Xiuzhen Zhang, V. Aksakalli, I. Hudson, Karin M. Verspoor, L. Cavedon   +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

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

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records

JAMA Network Open, 2022
Key Points Question What is the best method to predict which patients presenting to the emergency department will make a suicide attempt within 1 and 6 months after the visit?
M. Nock, A. Millner, E. Ross, Chris J. Kennedy, M. Al-Suwaidi, Yuval Barak-Corren, V. Castro, Franchesca Castro-Ramirez, Tess Lauricella, Nicole Murman, M. Petukhova, Suzanne A Bird, Ben Y. Reis, J. Smoller, R. Kessler   +14 more
semanticscholar   +1 more source

COVID-19 risk and outcomes in patients with substance use disorders: analyses from electronic health records in the United States

Molecular Psychiatry, 2020
The global pandemic of COVID-19 is colliding with the epidemic of opioid use disorders (OUD) and other substance use disorders (SUD) in the United States (US). Currently, there is limited data on risks, disparity, and outcomes for COVID-19 in individuals
Q. Wang, D. Kaelber, R. Xu, N. Volkow
semanticscholar   +1 more source

Machine learning approaches for electronic health records phenotyping: A methodical review

medRxiv, 2022
Objective: Accurate and rapid methods for phenotyping are a prerequisite to realizing the potential of electronic health records (EHRs) data for clinical and translational research.
Siyue Yang, Paul Varghese, E. Stephenson, K. Tu, Jessica L. Gronsbell   +4 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

Electronic health records to facilitate clinical research [PDF]

, 2016
Electronic health records (EHRs) provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Concerns have been raised about the increasing recruitment challenges in trials, burdensome
Blomster, Juuso I., Cowie, Martin R., Curtis, Lesley H., Duclaux, Sylvie, Ford, Ian, Fritz, Fleur, Goldman, Samantha, Janmohamed, Salim, Kreuzer, Jörg, Leenay, Mark, Michel, Alexander, Ong, Seleen, Pell, Jill P., Southworth, Mary Ross, Stough, Wendy Gattis, Thoenes, Martin, Zalewski, Andrew, Zannad, Faiez   +17 more
core   +2 more sources