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1 Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure

       Hidayet Takcı

      1.1 Introduction

      Heart diseases are the deadliest in the world. Of the many diseases included in the category of heart disease, the most prominent is coronary artery disease (CAD), which causes heart attacks. CAD, high blood pressure, and many other heart diseases cause heart failure (HF). With HF being a consequence of heart disease, the prediction of HF is related to the prediction of diseases categorized as heart disease.

      In this chapter, the diagnosis of HF is discussed in terms of invasive/non-invasive and artificial intelligence/machine learning techniques. Invasive and non-invasive techniques are distinct in the way the patient is treated. Invasive methods are usually associated with a physical intervention in the body. This intervention involves operations such as taking blood for blood analysis and not pressing strongly on the abdominal area. Non-invasive methods include physical therapy, taking blood pressure, and temperature measurement. In today’s world, where information technologies have evolved in every field, the field of health has also received its share. Computer-aided clinical decision support systems provide the strongest support for diagnostic studies today. The most important components of computer-aided diagnosis are artificial intelligence and machine learning systems that offer a wide range of services from smart assistant applications to imaging techniques. Artificial intelligence and machine learning have a healing role in electrocardiography, echocardiography, and similar invasive and non-invasive techniques.

In the second section of this chapter, HF will be described and its causes, symptoms, and treatment revealed. The third section will explain diagnosis by invasive and non-invasive methods. Computer-aided diagnosis and decision support systems are briefly mentioned in the fourth section. The fifth section looks first at what artificial intelligence is and then presents fields and examples of artificial intelligence supported studies. The sixth section explains machine learning, learning types, machine learning algorithms, and machine learning based diagnostic studies. The chapter’s concluding section summarizes studies and comments upon diagnostic studies for HF.

      1.2 Heart Failure

      HF belongs to a class of diseases that occur due to several diseases known as heart diseases and can be fatal if left untreated. In this section, HF is defined and the factors causing it, its symptoms, and its treatment are examined.

      1.2.1 What is HF?

      HF is sometimes known as congestive HF (CHF). HF is not a failure of the heart, but a condition in which the heart muscle cannot pump enough blood. It occurs due to, for example, narrowing of the coronary arteries, cardiovascular diseases, and high blood pressure.

      HF can occur at any age, but is more common in older people. Although it is not possible to cure the disease, some of its symptoms can be improved by the correct interventions. Conversely, faulty interventions will make the situation worse than before.

      The most common symptoms of HF are shortness of breath after movement or during rest, fatigue and weakness, swelling

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