Year: 2024
Type: article
Abstract: In the last few years, machine learning techniques have been attracting even greater attention in the field of diagnostics, particularly when detecting breast cancer. Relevant studies dedicated to machine learning techniques in breast cancer diagnosis were analyzed in three areas: solving secondary problems that occur in modern-day breast cancer diagnostics, role in an intelligent assessment of the patient’s condition for preliminary diagnostic decisions, and capability to detect breast cancer risk factors. The results revealed that machine learning techniques applied in breast cancer diagnosis have great potential for improving diagnostic accuracy and efficiency and solving secondary problems. The medical literature analysis has determined the parameters that are used as input data in machine learning techniques. Furthermore, the collected information will be applied to create a parameter system for breast cancer diagnosis using machine learning techniques.
Source: Digital Diagnostics
DOI: 10.17816/dd625866
Authors: Kirill S. Dyomin, Ilya V. Germashev
Institution: Volgograd State University
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402526638