AndrewNthale/Group-8-Phase-5-project

Identification of breast cancer from histopathological images using Image Classification in Kenya # IDENTIFICATION OF BREAST CANCER FROM HISTOPATHOLOGICAL IMAGES IN KENYA # **INTRODUCTION** Breast cancer stands as a formidable public health challenge in Kenya, characterized by alarmingly high mortality rates largely attributed to late-stage detection. The country's healthcare system grapples with limited resources, including a shortage of skilled pathologists and a dearth of advanced diagnostic technologies. Consequently, the prevailing manual diagnostic methods are time-consuming, error-prone, and often lead to delayed or inaccurate diagnoses. This project aims to address these critical issues by developing and implementing a robust machine learning model capable of accurately classifying breast cancer types from histopathological images. # **BUSINESS UNDERSTANDING** The overarching goal of this project is to address the critical issue of breast cancer in Kenya, characterized by high mortality rates due to late-stage detection and limited access to quality healthcare. By developing a deep machine learning-based solution, this aims to enhance early diagnosis, improve diagnostic efficiency, and expand access to accurate breast cancer screening services. Ultimately, this project seeks to contribute to a significant reduction in breast cancer mortality rates and improve the overall quality of life for Kenyan women. # **PROBLEM STATEMENT** Breast cancer poses a significant public health challenge, characterized by high mortality rates primarily due to late-stage detection. The country's healthcare system faces numerous obstacles in addressing this crisis, including limited access to specialized healthcare, a shortage of skilled pathologists, and a lack of advanced diagnostic technologies. Consequently, the current manual diagnostic process is time-consuming, error-prone, and often leads to delayed or inaccurate diagnoses. This delay in identifying and treating breast cancer has severe implications for patient outcomes, including increased morbidity and morta …