Artificial Intelligence, Machine Learning, and Data Science Technologies

Future Impact and Well-Being for Society 5.0

Neeraj Mohan, Ruchi Singla, Priyanka Kaushal, Seifedine Kadry, Neeraj Mohan, Ruchi Singla, Priyanka Kaushal, Seifedine Kadry

• Publisher: CRC Press
• Year: 2021
• Print ISBN:
  9780367720919
• eBook ISBN:
  9781000460544
• Topic: Technology & Engineering
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Technology & Engineering

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact.

The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other.

The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

1

Breast Cancer Diagnosis Using Machine Learning and Fractal Analysis of Malignancy-Associated Changes in Buccal Epithelium

Dmitriy Klyushin, Kateryna Golubeva, Natalia Boroday, and Dmytro Shervarly

DOI: 10.1201/9781003153405-1

Contents

1.1 Introduction

1.2Malignant-Associated Changes in Buccal Epithelium

1.3Materials and Methods of Morphometric Research and Image Analysis

1.4Fractal Analysis of Chromatin

1.4.1The Overall Algorithm for the Screening of Breast Cancer

1.5Results and Discussion

1.6Conclusion and Future Scope

References

1.1 Introduction

Currently, there is a constant increase in the incidence and death of breast cancer in women around the world. Consequently, the problem of early diagnosis and screening of breast cancer is very urgent. Early diagnosis of breast cancer involves the examination of large populations, so the screening method must be highly sensitive, specific and safe.

The currently accepted “gold standardˮ for breast cancer diagnostics includes clinical examination, mammography and aspiration biopsy. It allows for high diagnostic accuracy, but mammography implies radiation exposure, and aspiration biopsy is associated with tumor injury. This is contrary to the requirement for screening to be safe, so it is highly desirable to develop an effective screening method that is non-invasive and harmless. As such, we propose to use a non-invasive study of malignancy-associated changes (MAC) in the interphase nuclei of the buccal epithelium.

The purpose of the chapter is to describe a novel effective method for the screening of breast cancer based on the investigation of fractal properties of chromatin in Feulgen-stained nuclei of buccal epithelium using machine learning. The chapter consists of six sections. Section 1.1 is the introduction where the aim of the chapter and importance of the proposed method are described. Section 1.2 contains a short survey of papers on the malignancy-associated changes. In Section 1.3 we describe the morphometric research and image analysis of MAC in buccal epithelium. Section 1.4 describes the fractal analysis of the chromatin. Section 1.5 contains the results of diagnosis. Section 1.6 concludes our study and states some open problems.

1.2 Malignant-Associated Changes in Buccal Epithelium

The first reports on malignancy-associated changes (MAC) occurred in the 1960s, when the content of X-chromatin in somatic cells was widely studied and its lability was revealed during various functional changes in the body and general somatic pathology. In the presence of a tumor in the body, there are significant changes in the content of X-chromatin in the buccal epithelium and neutrophils of peripheral blood. It was shown that changes in the number of cells with X-chromatin are caused by disorders of the functional state of the heterocyclic X-chromosome.

Of particular interest are works showing changes in the epitheliocytes of the buccal epithelium in patients with tumors. Thus, in the 1960s H. Nieburgs and his co-authors (Nieburgs et al. 1962, Nieburgs 1968) reported a characteristic redistribution of chromatin masses in somatic cells in 77% of cancer patients and called these changes tumor-associated changes. The latter were characterized by an increase in the size of the nuclei of epitheliocytes, an increase in the size of the zones of “boundedˮ chromatin, which were surrounded by light zones. The same changes were observed in the cells of the liver, kidneys and other organs. In the paper (Obrapalska et al. 1973) it was reported that MAC was observed in the buccal epithelium of 74% of patients with malignant tumors. An increase in the content of DNA in the nuclei of epitheliocytes in patients with malignant melanoma in comparison with almost healthy women has been shown. At the same time, a decrease in the number of chromatin positive cells (X-chromatin) was found in patients with malignant melanoma compared with that in patients with benign nevi and in controls. An increase in the content of DNA and the size of the interphase nuclei of the buccal epithelium was found in patients with breast cancer. But some authors in cytospectrophotometric detection of the amount of DNA in the epitheliocytes of buccal epithelium in men with bronchial epithelioma did not find a significant difference between this indicator in sick and almost healthy men (Ogden et al. 1990).

Later, in the 1990s, in screening examinations of the population, in experimental conditions, and in a medical clinic the buccal epithelium of the oral cavity was used as a convenient object of study to detect early forms of disease (Rathbone et al. 1994, Rosin et al. 1...

Table of contents

• Cover
• Half Title
• Series Information
• Title Page
• Copyright Page
• Contents
• Preface
• Editor Biographies
• 1 Breast Cancer Diagnosis Using Machine Learning and Fractal Analysis of Malignancy-Associated Changes in Buccal Epithelium
• 2 Artificial Intelligence for Sustainable Health Care Advancements
• 3 Identification of Lung Cancer Malignancy Using Artificial Intelligence
• 4 Deep Learning in Content-Based Medical Image Retrieval
• 5 Implication of Image Pre-Processing in Object Detection Using Machine Learning Techniques
• 6 Forecasting Time Series Data Using Artificial Neural Network: A Review
• 7 Internet of Things: An Emerging Paradigm for Social Safety and Security
• 8 Artificial Intelligence: Encouraging Students in Higher Education to Seize Its Potential
• 9 Thermal Performance of Natural Insulation Materials for Energy Efficient Buildings
• 10 Maximum Power Point Tracking Techniques for PV Framework under Partial Shaded Conditions: Towards Green Energy for Smart Cities
• 11 Forecasting Energy Consumption Using Deep Echo State Networks Optimized with Genetic Algorithm
• 12 State-of-the-Art Natural Language Processing Techniques
• 13 Modern Approaches in HR Analytics towards Predictive Decision-Making for Competitive Advantage
• 14 Digital Transformation: Utilization of Analytics and Machine Learning in Smart Manufacturing
• 15 A Robust Cyber Security: Challenges and Opportunities
• Index