Thesis Abstract

**Abstract
** Skin cancer is one of the most prevalent types of cancer worldwide, with early detection being crucial for successful treatment. The use of Artificial Intelligence (AI) in dermatology has shown promising results in improving the accuracy and efficiency of skin cancer diagnosis and classification. This thesis investigates the application of AI in the field of dermatology specifically for diagnosing and classifying skin cancer. The research begins with an introduction to the background of the study, highlighting the importance of early detection of skin cancer and the potential benefits of AI in this context. The problem statement identifies the current challenges and limitations faced in traditional methods of skin cancer diagnosis. The objectives of the study are outlined to investigate how AI can enhance the accuracy and efficiency of skin cancer diagnosis and classification. The literature review delves into existing studies and technologies related to AI in dermatology, highlighting the advancements and challenges in the field. Various AI techniques such as machine learning, deep learning, and image analysis are explored in the context of skin cancer diagnosis. The research methodology section details the approach taken to collect and analyze data for this study. It includes the selection of datasets, the development of AI models, and the evaluation criteria used to measure the performance of the AI system in diagnosing and classifying skin cancer. The discussion of findings chapter presents the results of the study, showcasing the effectiveness of the AI system in accurately diagnosing and classifying different types of skin cancer. The limitations and challenges encountered during the research are also discussed, along with potential areas for future research and improvement. In conclusion, the study demonstrates the significant potential of AI in revolutionizing the field of dermatology, particularly in the diagnosis and classification of skin cancer. The findings highlight the importance of integrating AI technologies into clinical practice to enhance the accuracy and efficiency of skin cancer detection. This research contributes to the growing body of knowledge on the application of AI in healthcare and provides valuable insights for healthcare professionals, researchers, and policymakers in the field of dermatology.

Thesis Overview

The project titled "Application of Artificial Intelligence in Skin Cancer Diagnosis and Classification" aims to explore the integration of artificial intelligence (AI) technology in the field of dermatology to enhance the accuracy and efficiency of skin cancer diagnosis and classification. Skin cancer is one of the most common types of cancer globally, and early detection plays a crucial role in improving patient outcomes. Traditional methods of skin cancer diagnosis rely heavily on visual inspection by dermatologists, which can be time-consuming and subjective. The use of AI in dermatology has shown promising results in recent years, with machine learning algorithms demonstrating the potential to analyze skin images and detect cancerous lesions with high accuracy. By leveraging AI technology, this research seeks to develop a system that can assist healthcare professionals in diagnosing skin cancer more effectively, leading to earlier detection and improved patient care. The research will involve collecting and analyzing a large dataset of skin images, including benign and malignant lesions, to train and validate AI algorithms for skin cancer diagnosis. Various machine learning techniques, such as deep learning and image recognition, will be employed to extract features from the images and classify them into different categories based on their likelihood of being cancerous. Furthermore, the project will investigate the challenges and limitations associated with the implementation of AI in skin cancer diagnosis, such as data quality, interpretability of results, and integration with existing healthcare systems. The study will also consider ethical considerations related to patient data privacy and the role of AI as a decision support tool rather than a replacement for medical professionals. Overall, the research on the "Application of Artificial Intelligence in Skin Cancer Diagnosis and Classification" aims to contribute to the growing body of knowledge on the use of AI technology in healthcare, specifically in the field of dermatology. By developing a reliable and accurate AI system for skin cancer diagnosis, this project has the potential to revolutionize the way skin cancer is detected and treated, ultimately improving patient outcomes and reducing healthcare costs.