AI Applications for Diagnosis of Breast Cancer

49.5K

views

142

authors

22

articles

AI Applications for Diagnosis of Breast Cancer

49.5K

views

142

authors

22

articles

Editorial

17 October 2023

Editorial: AI applications for diagnosis of breast cancer

L. J. Muhammad

and

Alessandro Bria

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Editors

2

L. J. MUHAMMAD

Bayero University Kano

Alessandro Bria

Department of Electrical and Information Engineering, University of Cassino

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Artificial intelligence (AI) is rapidly gaining utility in the health sector, for example, for the diagnosis of various cancers such as Bladder Cancer, Breast Cancer, Colorectal Cancer, Kidney Cancer, and Lung Cancer among others. Useful AI techniques for this include expert systems, deep learning, Internet of Things (IoT), and nature-inspired techniques among others. There are advantages of using these techniques, for example, in order to imitate human decision-making with superior performance, an end-to-end learning scheme with integrated feature learning, and the capability of handling complex and multi-dimensional data and availability of clinical data from various high-throughput experiments. Therefore, medical consultants, researchers, and oncologists have seen a hope to devise and employ AI in various aspects of the diagnosis of cancer diseases. There is an immediate need for improved methods and tools that will enable AI Techniques to interface with available data/ information and guidance for clinical decision-making and treatments.

This Research Topic will focus on breast cancer diagnosis using medical image analysis and classification. The goal of this Research Topic is to examine current AI methodological and practical frameworks and come up with improved methods, approaches, frameworks and tools that will provide efficient AI-based Applications for the diagnosis of breast cancer. This Research Topic aims to improve the early diagnosis of breast cancer and screening techniques.

Potential themes include:
• Computer-aided diagnosis systems for breast cancer
• Deep convolutional neural networks for mammography cancer detection and classification
• Machine Learning/ Deep Learning/ Fuzzy Expert Systems and other AI-Based Techniques for cancer disease prediction, screening, and diagnosis
• ANNs in Breast Cancer Research (prediction, risk analysis, decision support systems, cancer radiological image analysis, etc)

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Editors

L. J. MUHAMMAD

Bayero University Kano

Alessandro Bria

Department of Electrical and Information Engineering, University of Cassino

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49,514 Total views

35,081 Article views

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1,314 Topic views

Published In

Frontiers in Artificial Intelligence

Medicine and Public Health

Frontiers in Oncology

Breast Cancer

Frontiers in Big Data

Medicine and Public Health

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