AI IN ONCOLOGY - DIFFERENTIATING BETWEEN BENIGN MASSES AND MALIGNANT TUMORS IN THE CASE OF BREAST CANCER

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.

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Publication Details

Journal
International Journal of Innovative Technologies in Social Science
Published
2025-09-26
DOI
https://doi.org/10.31435/ijitss.3(47).2025.3618
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

AI IN ONCOLOGY - DIFFERENTIATING BETWEEN BENIGN MASSES AND MALIGNANT TUMORS IN THE CASE OF BREAST CANCER

Paulina Gajniak, Patrycja Jędrzejewska-Rzezak, Aleksandra Winsyk, Monika Czekalska et al.
International Journal of Innovative Technologies in Social Science
Radiomics and Machine Learning in Medical Imaging
article

AI IN ONCOLOGY - DIFFERENTIATING BETWEEN BENIGN MASSES AND MALIGNANT TUMORS IN THE CASE OF BREAST CANCER

Paulina Gajniak, Patrycja Jędrzejewska-Rzezak, Aleksandra Winsyk, Monika Czekalska, Kinga Knutelska, Joanna Węgrzecka, Klaudia Bilińska, Tytus Tyralik, Maciej Karwat, Natalia Kulicka
article en

Abstract

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.

International Journal of Innovative Technologies in Social ScienceVol. 4(3(47))
John Paul II Catholic University of Lublin (PL), Poznan University of Medical Sciences (PL), Państwowa Wyższa Szkoła Zawodowa w Ciechanowie (PL), Cracow University of Technology (PL), Medical University of Lodz (PL), Ministry of the Interior (SI), 1 Military Clinical Hospital with Outpatient Clinic (PL), Academy of Physiotheray in Wrocław (PL), Cardinal Stefan Wyszynski University in Warsaw (PL)
Openalex Percentile: Top 61%
Radiomics and Machine Learning in Medical Imaging
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