Machine Learning-Based Approach for Early Diagnosis of Breast Cancer Using Biomarkers and Gene Expression Profiles

Sahu, Ankita; Qazi, Sahar; Raza, Khalid; Singh, Astha; Verma, Saurabh

doi:10.1007/978-981-16-9221-5_17

Cited by 9 publications

(1 citation statement)

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“…As illustrated in Figure 3, AI in the cancer research process is mainly divided into three parts: early and accurate diagnosis, cancer treatment, and prediction of cancer incidence, cancer recurrence, and cancer survival [35]. In the face of early cancer, doctors diagnose the patient's condition through various AI-based auxiliary detection means [36] AI, particularly machine learning algorithms, is deployed in the analysis of vast datasets, including mammograms, genetic information, and clinical records, to identify patterns and markers associated with breast cancer [37]. These algorithms can learn from diverse datasets, distinguishing between normal and abnormal findings, and assist healthcare professionals in diagnosing breast cancer at its early stages [38].…”

Section: Ai In Breast Cancer Diagnosis and Treatmentmentioning

confidence: 99%

Artificial Intelligence-based Mammogram Analysis for Early Detection

2023

Preprint

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The article focuses on breast cancer, mammography, and artificial intelligence. First, breast cancer is a widespread health problem that affects millions of people worldwide, and mammography is a widely adopted screening method. Then it introduced the advantages of mammography after AI participation, and introduced the importance of early detection of breast cancer and the application of artificial intelligence in breast cancer detection and treatment. From these aspects extend to the entire medical field of artificial intelligence issues. Several times throughout the paper, ethical issues that could arise from applying AI to healthcare are highlighted. At the end of the article, the paper describes the continued development of AI-based mammography analysis over the next period of time.

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