Cervical cancer predicting system using machine learning

dc.contributor.advisorKarunarathne B
dc.contributor.authorPrabodhani APKC
dc.date.accept2022
dc.date.accessioned2022
dc.date.available2022
dc.date.issued2022
dc.description.abstractMachine Learning has become a vital tool in everyday life, as well as a potent tool for automating most of the industries we want to automate. Machine Learning is a method of developing algorithms that learn from data, which might be labelled, unlabelled or learned from the environment. Machine Learning is employed in a variety of industries, including health care, where it provides much greater benefits through a proper decision and prediction processes. Because the machine learning in health care is scientific research, we must save, retrieve, and properly use information and data, as well as give knowledge about the difficulties that face the healthcare industry and proper decision-making. Over the years, these technologies have resulted in significant advancements in the health-care sector. Medical experts employ the machine learning tools and techniques to analyse medical data in order to identify hazards and provide accurate diagnosis and treatment. The paper aims to build a web application and put a trained machine learning model into production using Flask API. Here use cancer data to predict cervical cancer using machine learning. Therefore this project helps to use machine learning models for end-users or systems.en_US
dc.identifier.accnoTH4972en_US
dc.identifier.citationPrabodhani, A.P.K.C. (2022). Cervical cancer predicting system using machine learning [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21582
dc.identifier.degreeMSc In Computer Science and Engineeringen_US
dc.identifier.departmentDepartment of Computer Science and Engineeringen_US
dc.identifier.facultyEngineeringen_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21582
dc.language.isoenen_US
dc.subjectGUARANTEEING SERVICE - Job Scheduling Algorithmen_US
dc.subjectOBSERVATION BASED ADMISSION CONTROLen_US
dc.subjectTRIANGLE COUNT JOBSen_US
dc.subjectINFORMATION TECHNOLOGY -Dissertationen_US
dc.subjectCOMPUTER SCIENCE -Dissertationen_US
dc.subjectCOMPUTER SCIENCE & ENGINEERING -Dissertationen_US
dc.titleCervical cancer predicting system using machine learningen_US
dc.typeThesis-Abstracten_US

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