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Theorems on the Prevalence Threshold and the Geometry of Screening Curves

A Bayesian Approach to Clinical Decision-Making
BuchGebunden
377 Seiten
Englisch
Springererscheint am23.11.20242024
In Theorems on the Prevalence Threshold and the Geometry of Screening Curves, the author explores the mathematical underpinnings of screening and diagnostic testing, offering a unique and novel perspective which employs classical differential geometry and Bayesian theory to elucidate critical aspects of clinical decision-making.mehr

Produkt

KlappentextIn Theorems on the Prevalence Threshold and the Geometry of Screening Curves, the author explores the mathematical underpinnings of screening and diagnostic testing, offering a unique and novel perspective which employs classical differential geometry and Bayesian theory to elucidate critical aspects of clinical decision-making.
Details
ISBN/GTIN978-3-031-71451-1
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2024
Erscheinungsdatum23.11.2024
Auflage2024
Seiten377 Seiten
SpracheEnglisch
IllustrationenApprox. 150 p. 40 illus. in color.
Artikel-Nr.56560946
Rubriken
GenreMedizin

Inhalt/Kritik

Inhaltsverzeichnis
1. Introductory remarks on screening.- 2. Clinical judgement and decision-making.- 3. Bayes' theorem.- 4. Odds, probability and likelihood ratios.- 5. Prevalence threshold, screening curves and screening probability square plane S.- 6. Sequential Bayesian updating.- 7. Orthogonal Bayesian updating, parallel testing and asymptotic convergence.- 8. Theorems on the geometric definition of the positive likelihood ratio K.- 9. The screening paradox and dynamic systems.- 10. Performance metrics of binary classifiers.- 11. Applications in Bayesian epistemology and artificial intelligence (AI).- 12. What constitutes a sufficiently adequate binary classification system?.- 13. Gaussian distribution, confidence intervals, binomial (Wald) proportion, wilson score interval and delta theorem.- 14. Prevalence Threshold and Public Health.- 15. Shannon's entropy, Kullback-Leibler divergence, and mutual information in diagnostic systems.- 16. Estimating pretest probabilities.- 17. Case studies - clinical examples.- 18. Limitations and future directions.mehr

Autor


Dr. Jacques Balayla MD, MPH is a board-certified Obstetrician-Gynecologist. He obtained his medical degree from McGill University in 2012, where he went on to complete subspecialty training in Obstetrics and Gynaecology.  He is now a faculty lecturer and Osler fellow in the department of Obstetrics and Gynecology at McGill University and is a clinical investigator at the Lady Davis Institute (LDI) of the Jewish General Hospital in Montreal, Canada. During his training, Dr. Balayla obtained a certification in Human Genetics with distinction at Harvard University. Likewise, he graduated from the Clinician-Investigator Program (CIP) from the Royal College of Physicians and Surgeons of Canada with honours and obtained a Master of Public Health (MPH) degree with honours at the University of Montreal's School of Public Health (ESPUM).  Dr. Balayla has been active in clinical research for over 14 years and has been the recipient of numerous honours and recognitions for his work. Most notably, the Pregnancy Foundation, and the Society for Maternal-Fetal Medicine awarded Dr. Balayla the prestigious ``Quilligan Scholar title, for his promise as a future leader in Obstetrics and Perinatology. Dr. Balayla has also been recognized by the Quebec Medical Association (QMA) as the ``Emerging Medical Professional of the Year as well as by his Alma Matter, where he received the ``McGill Alumni Global (MAG) - Young Alumni Award" for having made extraordinary contributions to McGill University, fellow alumni and Society.
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