Results 251 to 260 of about 598,623 (310)

A call for ethical, equitable, and effective artificial intelligence to improve care for all people with epilepsy: A roadmap. A report by the ILAE Global Advocacy Council and Big Data Commission

Epilepsia, EarlyView.
Abstract The artificial intelligence (AI) revolution is upon us. It will inevitably form a central component of epilepsy workflows and patient advocacy. Therefore, it behooves us as health care providers to ride the crest of this wave and guide its direction for the benefit of all people with epilepsy.
Colin B. Josephson, Sandor Beniczky, Spiros Denaxas, Akio Ikeda, Lara Jehi, Angelina Kakooza Mwesige, Nathalie Jette, Gabriel Davis Jones, Philippe Ryvlin, Arjune Sen, Chahnez Charfi Triki, Gabriella Waters, Alla Guekht, J. Helen Cross   +13 more
wiley   +1 more source

Information Mode-Dependent Success Rates of Obtaining German Medical Informatics Initiative-Compliant Broad Consent in the Emergency Department: Single-Center Prospective Observational Study.

JMIR Med Inform
Hans FP, Kleinekort J, Boerries M, Nieters A, Kindle G, Rautenberg M, Bühler L, Weiser G, Röttger MC, Neufischer C, Kühn M, Wehrle J, Slagman A, Fischer-Rosinsky A, Eienbröker L, Hanses F, Teepe GW, Busch HJ, Benning L.   +18 more
europepmc   +1 more source

Quantifying the impact of a computer‐aided diagnostic score on the clinical diagnosis of functional seizures

Epilepsia, EarlyView.
Abstract Objective The diagnosis of functional/dissociative seizures (FDS) without ictal video‐electroencephalography is challenging. The Functional/Dissociative Seizures Likelihood Score (FSLS) is a machine learning‐based diagnostic score that aims to help clinicians identify FDS.
Wesley T. Kerr, Katherine N. McFarlane, Corinne H. Allas, Samuel W. Terman, Markus Reuber, Sung Hyun Seo, Payge Barnard, Adriana Y. Koek, Amir H. Karimi, Siddhika S. Sreenivasan, Jena S. Grauer, Di Sun, Meagan Watson, Elissa H. Patterson, James Castellano, Anto I. Bagić, L. Brian Hickman, Kenneth H. Kutschman, Laurence Knowles, Alistair Wardrope, Piyush Ostwal, Bridget K. MacDonald, Melissa Berry, Lomalan Reddy, Najda Robinson‐Mayer, Nicholas J. Beimer, Rachna Reddy, Sarah K. Yaghoubi, Laura A. Kirkpatrick, Danielle R. Carns, Alex J. Israel, Jamie D. Feusner, Zongqi Xia, Yanshan Wang, Laura A. Strom, Page B. Pennell, John M. Stern, Lubomir Hadjiiski, William C. Stacey   +38 more
wiley   +1 more source

Are single‐item global rating scales the same, better, or worse than multi‐item scales in epilepsy: A scoping review and meta‐analysis

Epilepsia, EarlyView.
Abstract Objective To examine the performance of single‐item global ratings (SIGRs) and multi‐item scales (MISs) in epilepsy research, and assess the influence of diverse constructs, study designs, and statistical methods. Methods Systematic scoping review following Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) and Joanna ...
Ann Subota, Mandavi Kashyap, Samuel Wiebe   +2 more
wiley   +1 more source

Comparative study of master's degree curricula in nursing informatics at Tehran University of Medical Sciences and the University of Maryland [PDF]

Elham Navab, Tooba Hoseini Azizi, Asieh Darvish   +2 more
openalex   +1 more source

L‐Relationship between uncertainty and average seizure frequency in clinical trials of antiseizure medications

Epilepsia, EarlyView.
Abstract Objective Antiseizure medications are approved based on clinical trials that demonstrate their efficacy as measured by reductions in seizure frequency (SF). When designing these trials, trialists must select inclusion criteria where SF can be reliably measured to maintain statistical power.
Wesley T. Kerr, Neo Kok, Katherine N. McFarlane, Advith S. Reddy, Lavanya Biju, Jacqueline A. French, Daniel M. Goldenholz   +6 more
wiley   +1 more source

Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics

, 2019

openalex   +1 more source

Comparative assessment of artificial intelligence chatbots' performance in responding to healthcare professionals' and caregivers' questions about Dravet syndrome

Epilepsia Open, EarlyView.
Abstract Objective Artificial intelligence chatbots have been a game changer in healthcare, providing immediate, round‐the‐clock assistance. However, their accuracy across specific medical domains remains under‐evaluated. Dravet syndrome remains one of the most challenging epileptic encephalopathies, with new data continuously emerging in the ...
Joana Jesus‐Ribeiro, Eugenia Roza, Bárbara Oliveiros, Joana Barbosa Melo, Mar Carreño   +4 more
wiley   +1 more source

Incorporating ChatGPT in Medical Informatics Education: Mixed Methods Study on Student Perceptions and Experiential Integration Proposals.

JMIR Med Educ
Magalhães Araujo S, Cruz-Correia R.
europepmc   +1 more source

Ambient technology in epilepsy clinical practice

Epilepsia Open, EarlyView.
Abstract The utilization of large language model‐based artificial intelligence (AI) in the field of neurology has gained attention as a viable tool to enhance and assist providers with processes ranging from scheduling patients to providing preliminary interpretations of testing results, pending orders, and documenting encounters. Epileptologists could
Haania Kakwan, Justin F. Rousseau, Lidia M. Moura, Irfan S. Sheikh   +3 more
wiley   +1 more source