AI IN ONCOLOGY - DIFFERENTIATING BETWEEN BENIGN MASSES AND MALIGNANT TUMORS IN THE CASE OF BREAST CANCER - Patrycja Jędrzejewska-Rzezak; Monika Czekalska; Natalia Kulicka; Kinga Knutelska; Aleksandra Winsyk; Paulina Gajniak; Maciej Karwat; Tytus Tyralik; Klaudia Bilińska; Joanna Węgrzecka (International Journal of Innovative Technologies in Social Science, 2025)
Introduction: Cancer poses a considerable challenge to worldwide healthcare systems. Presently, researchers globally are striving to enhance diagnostics and early diagnosis of the disease, which may decrease mortality rates among cancer patients and influence life expectancy. The application of artificial intelligence in medicine, especially in cancer diagnosis, signifies a substantial development. Radiomics plays a crucial role in this field, as it is utilized to augment the effectiveness of image processing for precise early breast cancer diagnosis and to boost overall treatment outcomes. Aim of the study: The main aim of this work is to clarify the essential ideas related to artificial intelligence, such as machine learning, deep learning, and radiomics, in a comprehensible way. Another aspect was to illustrate the great potential of employing this technology in cancer diagnostics, especially for breast cancer. Materials and methods: A review of the literature available in the PubMed database was performed, using the key words: „artificial intelligence", „machine learning" ; „deep learning”, „radiomics”, „breast cancer”, „cancer”, „oncology”. Conclusion: Artificial intelligence is prevalent in various domains, particularly in medicine, with a focus on oncological diagnosis. Its application can facilitate early disease detection and prompt treatment. Artificial intelligence possesses several limits, presenting a significant challenge for researchers in this domain. Further research on the advancement and enhancement of artificial intelligence methodologies is essential.