Artificial Intelligence in Breast Cancer Screening and Diagnosis

Abstract

Cancer is a disease that continues to plague our modern society. Among all types of cancer, breast cancer is now the most common type of cancer occurring in women worldwide. Various factors, including genetics, lifestyle, and the environment, have contributed to the rise in the prevalence of breast cancer among women of all socioeconomic strata. Therefore, proper screening for early diagnosis and treatment becomes a major factor when fighting the disease. Artificial intelligence (AI) continues to revolutionize various spheres of our lives with its numerous applications. Using AI in the existing screening process makes obtaining results even easier and more convenient. Faster, more accurate results are some of the benefits of AI methods in breast cancer screening. Nonetheless, there are many challenges in the process of the integration of AI that needs to be addressed systematically. The following is a review of the application of AI in breast cancer screening.

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer

“…Considering the prevalent discordance in HER2 status between primary and metastatic disease that affects a substantial portion of cases, it's prudent to consider evaluating the HER2-low status using metastatic tissues initially. This viewpoint suggests that optimizing AI models by training them on extensive HER2-stained datasets enriched with metastatic samples could enhance both precision and efficiency, thereby addressing subjectivity and variability concerns [ 18 ]. To ensure a comprehensive approach to interpreting HER2 IHC expression in the low range, ongoing education and updates remain vital components.…”

Exploring the human microbiome – A step forward for precision medicine in breast cancer

“…The potential of these AI techniques is immense in unveiling critical insights into the role of the microbiome in human health and developing personalized treatments. Specifically, in the context of breast cancer, AI can revolutionize diagnostics and therapeutics by identifying microbial biomarkers associated with subtypes or treatment outcomes 128,129 . This information can facilitate personalized therapies targeting specific microbial communities, and AI algorithms can predict patients' response to breast cancer treatments, thus minimizing side effects.…”

A Review on Prediction Model for Breast Cancer Using Machine Learning

“…There is a need for a proper feature selection technique which can consider maximum genetic anomaly simultaneously and efficiently [6].Since breast cancer is a complex disease and its complexity differs from person to person so one cannot depend on a generalized medication. Hence, there should be a criteria which should have scalable drug sensitivity.…”

“…There are many techniques that have been introduced in the field of breast cancer prediction. Techniques such as deep learning [4], machine learning [5], and artificial intelligence [6]. Several ML techniques, including Support Vector Machine [7], Genetic [8], and classification techniques, are used to predict breast cancer.…”