Introduction:
Cardiovascular diseases cause a significant number of deaths globally. Rapid economic development has led to drastic changes in lifestyle and many environmental risk factors contributing to heart diseases. Unfortunately, there is a yearly increase in the number of people diagnosed with cardiovascular disease. To overcome this situation, scientists have introduced AI (artificial intelligence) to improve the strategy for diagnosing and treating heart diseases. This article describes the prediction of heart diseases and treatment using artificial intelligence. We can reduce the death rate through proper management. The coronary care unit aims to provide patients with a high standard of care. A special hospital unit called the cardiac intensive care unit treats serious and acute cardiac patients. It is a specialized unit for heart disease patients who need constant care and support for a speedy recovery. Patients admitted to the cardiac intensive care unit for unstable and serious cardiac conditions require full-time care and monitoring. There are various opportunities in the hospital setting to apply artificial intelligence. AI technology can decode massive amounts of data in electronic health records; otherwise, time-consuming and laborious. Tools are developed to interpret this information from patient charts and identify diseases.
What Is Artificial Intelligence and Machine Learning?
The significance of artificial intelligence and machine learning are as follows:
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In computer science, artificial intelligence is machines that mimic and replicate human intelligence.
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This technology can be applied to the management of critically ill patients.
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Datasets are used to predict the length of the stay, mortality rates, and risk of developing medical complications or conditions such as sepsis and ARDS (acute respiratory distress syndrome).
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The development of intelligent machine learning monitors the human response to critical illness with a high degree of certainty.
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One of the fundamental challenges faced in the case of the critically ill is the management of huge amounts of information generated by the patients.
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In intensive care units equipped with electronic information systems, hundreds of structured information elements are collected daily in an electronic chart, including vital signs, basic and advanced monitoring records, laboratory data, and drug prescriptions.
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The main aim of artificial intelligence is to replace human intelligence to accomplish critical tasks on par with humans in a short period.
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Physicians who know about artificial intelligence can evaluate how to improve their work with AI, which will benefit them since AI can assist them in various necessary procedures. A branch of artificial intelligence, machine learning, permits a machine to analyze and arrive at a solution through in-depth analysis of historical data.
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Machine learning also includes deep learning. Deep learning is a method that enables the algorithm to program automatically and learn from big data.
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A cardiac care unit is a specialized ward designed to treat patients with chronic illnesses or severe heart diseases. After treatment or surgery, people are shifted to the CICU (cardiac intensive care unit) to prevent death due to heart disease. For this reason, it is developed in many hospitals.
AI's goal is to overcome the shortcomings of the current medical systems:
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Misdiagnosis by primary clinicians.
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High medical expenses.
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Long training time for doctors.
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Uneven distribution of senior physicians or clinicians.
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Shortage of physicians in undeveloped areas.
What Are the Conditions That Are Managed in the Cardiac Intensive Care Unit?
The following conditions are managed in the CICU-
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Those with serious heart diseases such as cardiac arrhythmia (improper electrical impulses in the heart), heart attack, myocardial infarction (a blockage in the heart’s blood vessels), unstable angina (no sufficient blood and oxygen supply to the heart), chronic stable angina (chest pain), and congenital heart disease.
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Coronary artery bypass surgery (a procedure to treat coronary artery disease and help restore blood flow to the heart by creating a new route around the blockage for the blood to pass), valvular surgery, and heart transplantation. The team also manages patients with secondary conditions such as respiratory disease, septic infection, kidney disease, and diabetes.
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Those who have serious burns.
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Difficulty in breathing.
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Patients with organ failure.
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Individuals are suffering from a life-threatening infection.
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Patients in a state of coma.
The patients in the CICU have various complications, such as respiratory failure and renal failure. The paramedical staff should be capable of practicing and providing the best patient health care and management. Heart diseases, including vascular diseases, and patient admission to CICU are increasing yearly. There are numerous opportunities in the hospital setting to apply AI models. The technology is designed to extract information from patients' charts and identify high-cost patients. Their automated pattern allows supervised machine learning algorithms to recognize images used extensively in surgery. AI is being used to program computers to process and develop data quickly for better treatment outcomes, monitoring of the heart, detecting arrhythmia, and developing AI technology for smartphones and high-tech stethoscopes, etc. In the current era of big and real-world data, the huge and heterogeneous amount of information being streamed from CICU provides immense possibilities for AI technology in this field.
What Are the Applications of AI in the CICU?
Recent machine learning studies in cardiac imaging have significantly progressed to provide us with auto interpretation and auto quantification in echocardiography, single photon emission computed tomography, and cardiac MR, among others. The cardiac ward provides highly quantifiable information on cardiac functions, valvular diseases, blood flow, perfusion, and vascular anatomy. The applications of AI in CICU are:
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Medical Imaging - Therapeutic are collected and used methodically that are readily available for AI systems. The cost and time associated with examining can be reduced by AI, allowing more target treatment.
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Surgery - AI- automated tools have been used in research to complete complex tasks in keyhole surgery as tying knots to close injuries.
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Helping People Who Have Had a Stroke - People who come in with an intracerebral hemorrhage take a CT scan in emergency rooms. That scan is examined by a computer-trained program to analyze computed tomography data, which cuts the time for diagnosis and limits brain damage.
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Reducing Heart Problems - Applying AI in ECGs has resulted in a low-cost test that can predict the presence of a weak heart pump, thus preventing heart failure. All patient information is removed to protect privacy. This data can predict heart failure noninvasively, inexpensively, and within seconds.
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Detecting Atrial Fibrillation Sooner - AI-guided ECGs are also used to detect abnormal heart rhythms (atrial fibrillation).
Conclusion:
AI can help deal with rapidly increasing global cardiovascular problems. With the right clinical knowledge and skills, physicians can successfully treat with the help of AI. However, AI cannot completely replace humans; instead, it can fasten the process.
