Applying Bayesian Networks to Help Physicians Diagnose Respiratory Diseases

Applying Bayesian Networks to Help Physicians Diagnose Respiratory Diseases

Presented at the 10th Annual BayesiaLab Conference on Friday, October 28, 2022.


The differential diagnosis of respiratory diseases is usually a challenge for medical specialists in the first line of care, which has increased under the current COVID-19 pandemic. A Clinical Decision Support System — CDSS — is being developed using Bayesian Networks – BNs – to help physicians diagnose respiratory diseases, including those related to COVID-19. Network structure has been elicited from expert physicians, and network parameters (disease prevalence, symptoms, findings, and lab results conditional probabilities) were extracted from relevant bibliography or currently standard global information sources. The CDSS is being tested using case studies taken from real situations, provided and validated by physicians. The resulting system demonstrates the suitability and flexibility of BNs for diagnosis support.

Presentation Video

Presentation Slides

About the Presenters

Dr. Ernesto Ocampo, Ph.D.

Dr. Ernesto Ocampo, Ph.D., is a senior full-time professor at the Catholic University of Uruguay Computer Science Department, where he teaches subjects such as Artificial Intelligence, Machine Learning, and Algorithms. His research focus is on Artificial Intelligence applied to Clinical Decision Support Systems (e.g., Acute Bacterial Meningitis, HIV/AIDS, respiratory diseases, and cancer).

His background is in software engineering and holds a Ph.D. in Computer Science from the University of Alcalá, Spain.

An IEEE Senior Member, Dr. Ocampo has worked in the software industry for more than 30 years, currently as a technical consultant for Qualisys Software and Technologies - (opens in a new tab)).

Dr. Silvia Herrera, MD

Dr. Silvia Herrera, MD, is a senior pediatric physician with more than 30 years of professional experience. Dr. Herrera worked for 25 years as an internal pediatrician in the Central Armed Forces Hospital of Uruguay, and for several years she was part of the pro-bono health team that focused on children with HIV/AIDS at the National Pediatric Centre of Reference.

She currently works in a pre-hospital pediatric emergency unit and the pediatric emergency room of a private health provider hospital.

Dr. Herrera has helped the UCU Computer Science Department for several years as a field expert in various CDSS research projects.

Juan Francisco Kurucz, Eng.

Juan Francisco Kurucz is an Informatics Engineer who graduated from the Catholic University of Uruguay, where he works as an assistant professor in Artificial Intelligence and other computer science courses. He is an active academic researcher on Artificial Intelligence and is currently focused on the application of Bayesian Networks and Deep Learning to Clinical Decision Support.

In the professional field, Juan Francisco works as a Machine Learning Engineer at an AI Software Company —Tryolabs — where he specializes in Computer Vision. He also participates in the IEEE as a volunteer member.

Lucas Lois, Eng.

Lucas Lois is a Software Engineer who graduated from the Catholic University of Uruguay, where he works as an assistant professor in Computer Science courses. His research area is Artificial Intelligence in Health, focused on the application of Natural Language Processing to Named Entities Recognition in Electronic Health Records and Bayesian Networks applied to Clinical Decision Support.

In the professional field, Lucas also has several years of software development experience, working currently as a software team leader at December Labs, a high-touch boutique Design & Development shop.

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