Thesis Abstract

Abstract
Skin cancer is a prevalent form of cancer that affects millions of individuals worldwide. Early detection and monitoring of skin cancer are crucial for successful treatment outcomes. This thesis presents the development of a mobile application aimed at assisting users in detecting and monitoring skin cancer. The mobile application utilizes advanced image processing and machine learning algorithms to analyze images of skin lesions and provide users with real-time feedback on the likelihood of skin cancer. Chapter 1 provides an introduction to the research topic, discusses the background of the study, and presents the problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter 2 comprises a comprehensive literature review covering ten key topics related to skin cancer detection, mobile health applications, image processing, and machine learning. Chapter 3 outlines the research methodology employed in the development of the mobile application. This chapter includes detailed descriptions of the data collection process, image processing techniques, machine learning algorithms, app development tools, validation methods, and ethical considerations. The research methodology aims to ensure the accuracy and reliability of the mobile application in detecting and monitoring skin cancer. Chapter 4 presents an in-depth discussion of the findings obtained from the development and testing of the mobile application. The chapter highlights the performance metrics, user feedback, challenges faced during development, and potential areas for future improvement. The discussion emphasizes the importance of user-friendly interfaces, accurate image analysis algorithms, and real-time monitoring capabilities in enhancing the effectiveness of the mobile application. Chapter 5 concludes the thesis by summarizing the key findings, discussing the implications of the research, and providing recommendations for future work. The mobile application for skin cancer detection and monitoring shows promising results in assisting users with early detection and continuous monitoring of skin lesions. The potential impact of the mobile application in improving access to skin cancer screening and reducing healthcare disparities is also discussed. Overall, this thesis contributes to the field of dermatology by introducing an innovative mobile application for skin cancer detection and monitoring. The development of this mobile application has the potential to empower users in taking proactive steps towards skin cancer prevention and early intervention, ultimately leading to improved healthcare outcomes and quality of life.

Thesis Overview

The project titled "Development of a Mobile Application for Skin Cancer Detection and Monitoring" aims to address the growing concern of skin cancer by leveraging mobile technology for early detection and continuous monitoring. Skin cancer is a significant public health issue globally, with increasing incidence rates and mortality rates. Early detection plays a crucial role in improving treatment outcomes and reducing morbidity associated with skin cancer. The research will focus on developing a mobile application that utilizes image recognition technology to analyze skin lesions and provide users with real-time feedback on the likelihood of skin cancer. By harnessing the power of artificial intelligence and machine learning algorithms, the application will be able to classify skin lesions accurately and assist users in determining the next steps for evaluation and treatment. Furthermore, the mobile application will incorporate features for users to track changes in their skin over time, enabling continuous monitoring and early detection of any suspicious developments. This proactive approach to skin cancer detection can empower individuals to take control of their skin health and seek medical attention promptly when necessary. The research overview will explore the technological aspects of developing the mobile application, including image processing techniques, machine learning model training, and user interface design considerations. Additionally, the project will investigate the feasibility and accuracy of the application in detecting various types of skin lesions and differentiating between benign and malignant cases. Overall, the "Development of a Mobile Application for Skin Cancer Detection and Monitoring" project represents an innovative and practical solution to improve skin cancer awareness, early detection, and monitoring using mobile technology. By providing users with a user-friendly and reliable tool for skin health management, the research aims to contribute to reducing the burden of skin cancer and enhancing overall public health outcomes.