Results 131 to 140 of about 635,446 (241)

The Effect of Virtual Training Course of Brain Diseases and Pathologies CT Scan Interpretation on the Rate of Accurate Diagnosis by Medical Students. [PDF]

Adv Biomed Res
Azizkhani R, Mousakazemi M, Zamani M, Najimi A, Jafarpisheh MS, Forghani M.   +5 more
europepmc   +1 more source

Rheumatoid Arthritis and Coronary Artery Calcium Progression: A Case Cohort Analysis From ELSA‐Brasil

Arthritis Care &Research, EarlyView.
Objective To investigate the association between rheumatoid arthritis (RA) and coronary artery calcium (CAC) prevalence, incidence, and progression over four years in adults without prior cardiovascular disease. Methods A case‐cohort study within the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil) included 585 participants (86 patients with ...
Patrícia Fonseca Estrada, Marcos Rafael N. Cavalcante, Itamar de Souza Santos, Márcio S. Bittencourt, Vandrize Meneghini, Paulo A. Lotufo, Alessandra C. Goulart, Isabela M. Bensenor   +7 more
wiley   +1 more source

Short-term simulation training course improves basic obstetric ultrasound operational skills of residents: A multi-center study. [PDF]

PLoS One
Zhao Y, Zhou P, Tang X, Zhu W, Liu W, Zhou J, Wang J, Luo Y, Zhang J, Yang L, Xu Y.   +10 more
europepmc   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

Arthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein, Jennifer L. F. Lee, Evelyne Vinet, Arielle Mendel, Christian A. Pineau, Fares Kalache, Louis‐Pierre Grenier, Sasha Bernatsky   +7 more
wiley   +1 more source

TRAINING COURSES

Episodes, 1984
  +7 more sources

Empowering early detection: a pioneering breast health training course for healthcare workers in Malawi. [PDF]

BMJ Glob Health
Pittalis C, Chalulu K, Banda JC, Chisala P, Algheffari J, Mwandira R, Gajewski J, Schouten E.   +7 more
europepmc   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Understanding the Burden of Orofacial Involvement and Patient Treatment Preferences in Systemic Sclerosis: Results From a Large International Survey

Arthritis Care &Research, EarlyView.
Objective Orofacial manifestations are significantly impactful in patients with systemic sclerosis (SSc) yet remain understudied, with no dedicated clinical guidelines to inform their management. Methods An international online survey comprised38 questions addressing orofacial manifestations of SSc, including patients’ confidence in their treating ...
Eleni Deligianni, Lee Shapiro, Deana Gibbs, Zsuzsanna H. McMahan, Michael Hughes   +4 more
wiley   +1 more source

Characterization of five environmental phages infecting <i>Escherichia coli</i> K-12 isolated during a phage biology training course. [PDF]

Microbiol Spectr
Shyrokova L, Egorov AA, Cole A, Duque-Pedraza JJ, Tyagi A, Ernits K, Mets T, Kurata T, Juozapaitis J, Yang ALJ, Ibarra Chavez R, Graversgaard Henriksen FO, Lassen S, Atkinson GC, Hauryliuk V, Johansson MJO.   +15 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source