International Research Journal of Education and Technology

Histopathologic cancer detection using artificial intelligence (AI) holds immense potential for revolutionizing cancer diagnosis and treatment. This paper presents an overview of the current landscape, challenges, and opportunities in leveraging AI for histopathologic analysis in cancer detection. With advancements in machine learning and deep learning techniques, AI algorithms can analyze histopathologic images with unprecedented accuracy and efficiency, aiding in the early detection of cancerous lesions, personalized treatment planning, and improved patient outcomes. However, the feasibility of AI-powered cancer detection relies on

factors such as data availability, algorithm development, regulatory compliance, clinical integration, cost-effectiveness, ethical considerations, and long-term sustainability. Addressing these challenges requires interdisciplinary collaboration among data scientists, medical professionals, regulators, and industry stakeholders. By overcoming these hurdles, AI has the potential to transform histopathologic cancer detection into a more objective, efficient, and accessible process, ultimately contributing to advancements in cancer care and research.

Keyword: Artificial intelligence, algorithm, Histopathology, machine learning.