Predicting Heart Failure

Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods

Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, Issam Bait Bahadur, Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, Issam Bait Bahadur

• Verlag: Wiley
• Jahr: 2022
• ISBN:
  9781119813033
• Auflage: 1
• Thema: Medicine
• Thema: Cardiology

PREDICTING HEART FAILURE

Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it.

This book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. Predicting Heart Failure supplies readers with trustworthy insights into all aspects of heart failure, including essential background information on clinical practice guidelines, in-depth, peer-reviewed articles, and broad coverage of this fast-moving field. Readers will also find:

• Discussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application
• Summary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology
• Coverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure
• Discussion of the risks and issues associated with the remote monitoring system
• Assessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection
• Artificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations.

Providing the latest research data for the diagnosis and treatment of heart failure, Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.

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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 in the ankles and legs, disturbed heartbeat, persistent cough, and dizziness and the like. Symptoms can develop rapidly (acute HF) or gradually over weeks (chronic HF).

With early intervention for HF, it will be possible for patients to live longer. Some measures such as losing weight, reducing stress, and reducing the amount of salt used will positively affect the quality of life of patients. One way to prevent HF is to prevent and control conditions such as CAD, high blood pressure, diabetes, and obesity.

The activity that will benefit most is diagnosing the disease and conducting studies according to the symptoms. Thus, as in many other diseases, early diagnosis will have a life-saving effect in HF, as will correct diagnosis and determining the type and real cause of the ailment.

1.2.2 Causes of HF

As mentioned, the causes of HF are CAD, high blood pressure, and other heart diseases, and it occurs because of the damage to the heart muscle brought about by these and similar conditions. While oxygen is regularly carried to a normal heart, it is not possible to carry enough oxygen in the case of a damaged heart. Although HF usually occurs on the left side of the heart, it can develop on the right or both sides. Table 1.1 lists multiple HF types and their results.

Table 1.1 HF types and their outcomes.

HF Type	Outcome
Left-sided HF	This causes fluid to accumulate in the lungs, which causes shortness of breath in people.
Right-sided HF	Fluid builds up in the abdomen, legs, and feet, which causes swelling in the abdomen and legs.
Systolic HF	This occurs when the heart muscle cannot contract strongly as it should; as a result, blood is not pumped in the normal way.
Diastolic HF	There is insufficient blood filling the area due to the inability of the heart to relax sufficiently.

Some of the prominent causes of HF are:

• CAD and heart attack: CAD is the most prominent heart disease and the most common cause of HF. The disease occurs when blood circulation is not normal due to fat deposits, called plaques, in the blood vessels. Heart attacks are divided into mild heart attack and major heart attack. Mild heart attacks occur in a small portion of the heart muscle. However, a mild heart attack should be taken seriously because it can cause a second attack. Major heart attack affects a large part of the heart muscle. The blood flow to the heart is completely blocked or there is no blood flow for a long time. Major heart attack can cause cardiac arrest and death.
• High blood pressure (hypertension): High blood pressure is one of the factors that makes it difficult for the heart to pump blood to the body. This strain causes the heart muscle to work more than normal, damaging it.
• Faulty heart valves: The function of the heart valves is to keep the blood flowing in the right direction. Failure of heart valves to function is known as heart valve malfunction. Heart valve malfunctions can be caused by genetic factors, old age, and infection. A faulty valve tires the heart, forcing it to work harder and causing it to weaken over time.
• Damage to the heart muscle (cardiomyopathy): Cardiomyopathy can have many causes, such as various diseases, infections, alcohol use, and the toxic effect of drugs like cocaine or chemotherapy drugs. Sometimes it can be due to genetic factors.
• Heart muscle inflammation: This is caused by viruses and can lead to left-sided HF.
• Congenital heart defects: If the heart and chambers or valves aren’t formed correctly, the healthy parts of the heart have to work harder to pump blood, which can lead to HF.
• Heart arrhythmias: Abnormal heart rhythms will show heart-damaging output in both fast heartbeat and slow heartbeat. Its rapid beating will tire the heart, and its slow beating will cause problems in circulation.
• Other diseases: Diabetes, HIV, hyperthyroid and similar diseases can also cause HF.

Heart diseases and the factors that affect the HF that occur as a result may be genetic, sometimes congenital abnormalities, and sometimes related to our lifestyle. Overweight, having a sedentary life, smoking, and stressful work life are also harmful factors for the heart [1].

1.2.3 What are the Symptoms of HF?

HF may be faced if one or more of the following symptoms are present. For example, if someone is tired earlier than before even though they are doing the same activity, this might be a symptom. This symptom should not be confused with early fatigue due to old age – a 55-year-old person should compare and interpret their symptoms ac...