Thesis Abstract

Abstract
Skin cancer is a significant public health concern worldwide, with early detection playing a crucial role in improving patient outcomes. This thesis presents the development of a mobile application aimed at enhancing the detection and monitoring of skin cancer. The mobile application utilizes advanced image processing algorithms and artificial intelligence techniques to analyze skin lesions and provide users with real-time feedback on the likelihood of malignancy. The research begins with a comprehensive review of existing literature on skin cancer detection methods and mobile health applications. The literature review highlights the limitations of current approaches and underscores the need for innovative solutions to improve early detection rates and facilitate remote monitoring of skin lesions. The methodology section details the design and development process of the mobile application, including the selection of image processing algorithms, machine learning models, and user interface design considerations. The research methodology also outlines the data collection process, validation techniques, and ethical considerations involved in testing the mobile application with real-world users. The findings section presents the results of user testing and validation studies, demonstrating the effectiveness and accuracy of the mobile application in detecting and monitoring skin cancer. The discussion delves into the implications of the findings, including the potential impact on improving early detection rates, empowering users to take proactive measures in skin health management, and reducing healthcare disparities in underserved populations. In conclusion, the thesis summarizes the key contributions of the research, including the development of a novel mobile application for skin cancer detection and monitoring, the validation of its effectiveness through user testing, and the potential for widespread adoption to improve public health outcomes. The study underscores the importance of leveraging technology to address critical healthcare challenges and presents a promising tool for enhancing skin cancer detection and monitoring practices.

Thesis Overview