dc.contributor.advisor |
Chehab, Ali |
dc.contributor.author |
Kaheel, Hussein |
dc.date.accessioned |
2021-05-05T05:46:37Z |
dc.date.available |
2021-05-05T05:46:37Z |
dc.date.issued |
5/5/2021 |
dc.identifier.uri |
http://hdl.handle.net/10938/22452 |
dc.description |
Prof. Rouwaida Kanj
Prof. Ibrahim Issa
Dr. Ali Hussein |
dc.description.abstract |
Recently, the healthcare system is facing strenuous challenges in terms of supporting the ever-increasing number of patients and associated costs due to the COVID-19 spread. Thus, the recent impact of COVID-19 mandates a shift in the healthcare sector mindset. As such, it becomes essential to benefit from modern technology, such as Machine Learning, in order to design and develop intelligent and autonomous healthcare solutions. In this context, researchers tried to fight COVID-19 by proposing Artificial Intelligence (AI)-based solutions. Several companies around the world provided a set of AI-based solutions during the last month to detect COVID-19, based on chest CT or X-ray scans. The main goal of this thesis is to design and develop a fast, efficient and reliable technique to detect
COVID-19 based on Deep Learning, which is used to develop medical diagnosis in line with the initial objective. |
dc.language.iso |
en_US |
dc.subject |
COVID-19, Corona Score, Medical Imaging Analysis, AI Medical Platform , Deep Learning, Computed Tomography (CT), Segmentation |
dc.title |
AI-Based Medical Image Analysis for Early COVID-19 Detection |
dc.type |
Thesis |
dc.contributor.department |
Department of Electrical and Computer Engineering |
dc.contributor.faculty |
Maroun Semaan Faculty of Engineering and Architecture |
dc.contributor.institution |
American University of Beirut |