Results 11 to 20 of about 475,340 (247)

Pre-test Probability Scores in Patients with Obstructive Sleep Apnea

Journal of Advanced Lung Health
Introduction: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that significantly impacts both quality of life and cardiovascular health. Various pretest probability scores are employed to identify high-risk patients before formal diagnostic ...
Magizh Samuel, Ketaki Utpat, Dipika Koli, Unnati Desai   +3 more
doaj   +2 more sources

Pre-test probability and likelihood ratios for clinical findings in canine leishmaniasis. [PDF]

Transbound Emerg Dis, 2022
Canine leishmaniasis is a parasitic zoonosis mainly caused by L. infantum; an obligate intracellular protozoan transmitted by haematophagous insects of the genus Phlebotomus, which affects dogs and wild canids. The clinical implications of this disease are highly variable, since infected animals may remain asymptomatic (absence of observable clinical ...
Galán-Relaño Á, Maldonado A, Gómez-Gascón L, Tarradas C, Astorga RJ, Luque I, Huerta B.   +6 more
europepmc   +5 more sources

One step closer to quantifying 'clinical likelihood' in pre-test probability. [PDF]

Eur Heart J Qual Care Clin Outcomes, 2022
Weir-McCall JR, Williams MC, Wood A.
europepmc   +3 more sources

Subjectivity of pre-test probability value: controversies over the use of Bayes' Theorem in medical diagnosis. [PDF]

Theor Med Bioeth, 2023
AbstractThis article discusses the use of Bayes’ Theorem in medical diagnosis with a view to examining the epistemological problems of interpreting the concept of pre-test probability value. It is generally maintained that pre-test probability values are determined subjectively.
Rzepiński T.
europepmc   +3 more sources

Assessment of Pre-test and Clinical Probability in the Diagnosis of Chronic Coronary Syndrome — What's New?

Рациональная фармакотерапия в кардиологии, 2022
In the 2019 European Society of Cardiology (ESC) guidelines, the diagnostic algorithm for chronic coronary syndrome (CCS) was significantly changed, a significant revision of the pretest probability assessment scale (PTP) was made, an assessment of the ...
A. N. Sumin, A. V. Shcheglova
doaj   +1 more source

Development and Internal Validation of a Predictive Model for Adult GH Deficiency Prior to Stimulation Tests

Frontiers in Endocrinology, 2021
BackgroundThe diagnosis of adult GH deficiency (GHD) relies on a reduced GH response to provocative tests. Their diagnostic accuracy, however, is not perfect, and a reliable estimation of pre-test GHD probability could be helpful for a better ...
Fabio Bioletto, Mirko Parasiliti-Caprino, Alessandro Maria Berton, Nunzia Prencipe, Valeria Cambria, Ezio Ghigo, Silvia Grottoli, Valentina Gasco   +7 more
doaj   +1 more source

Estimating Pre-Test Probability of Coronary Artery Disease: Battle of the Scores in an Evolving CAD Landscape. [PDF]

JACC Cardiovasc Imaging, 2019
Di Carli MF, Gupta A.
europepmc   +2 more sources

Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability. [PDF]

JAMIA Open
Abstract Objective To evaluate large language models (LLMs) for pre-test diagnostic probability estimation and compare their uncertainty estimation performance with a traditional machine learning classifier.
Gao Y, Myers S, Chen S, Dligach D, Miller T, Bitterman DS, Chen G, Mayampurath A, Churpek MM, Afshar M.   +9 more
europepmc   +3 more sources

Derivation and validation of a scoring system to assess pre-test probability of being COVID-19 positive. [PDF]

J Infect, 2021
No abstract ...
Borghetti A, Ciccullo A, Paratore M, Rovedi F, Stella L, Marchetti A, Marchetti A, Cattani P, Zileri Dal Verme L, Cauda R, Gasbarrini A, Gasbarrini A, Di Giambenedetto S, Residents against COVID-Unit Elite (ResCUE)-Team.   +13 more
europepmc   +6 more sources

Machine learning for assessing the pretest probability of obstructive and non-obstructive coronary artery disease

Российский кардиологический журнал, 2020
The review presents an analysis of publications on use of machine learning (ML) to assess the pretest probability of obstructive and non-obstructive coronary artery disease (CAD). Data on the high prevalence of non-obstructive CAD among patients referred
B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev   +3 more
doaj   +1 more source