Development of a visualization system for neural network results on medical images

Borovets, Andrii

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Факультет прикладних наук
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Бакалаврська програма "Комп'ютерні науки"
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2020
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dc.contributor.author	Borovets, Andrii
dc.date.accessioned	2024-02-15T09:50:39Z
dc.date.available	2024-02-15T09:50:39Z
dc.date.issued	2020
dc.identifier.citation	Borovets, Andrii. Development of a visualization system for neural network results on medical images / Borovets, Andrii; Supervisor: Oles Dobosevych; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2020. – 35 p.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4522
dc.language.iso	en	uk
dc.title	Development of a visualization system for neural network results on medical images	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Heart stenosis corresponds to a frequent problem with the heart arteries when the valve is getting too narrow and does not open properly. The flaps of a valve may become thicker or bound together, and as a result, preventing the valve from fully opening. This problem can be detected and treated, if diagnosed in time. To deter- mine if patients’ conditions are critical or not – may require a significant amount of time of the doctor. Diagnosis timing is one of the most critical factors with this particular disease, frequently determining the outcome for the patient. Considering the current general medical service practice, there is no apparent way to create a prioritized patients list, so that patients with more critical or urgent conditions could be treated first. In this project I worked on a web application that would accept the MPR im- ages from a user(doctor) and feed these images to a Neural network algorithm that would predict the state of the patient and prioritize the list of patients for the doctor. The app also has a very intuitive and self-explanatory probability chart to facilitate doctor’s review of each patient’s case. Altogether, the app is expected to address the problem of making urgent stenosis cases apparent to the doctor.	uk