Artificial intelligence (AI) is a technology that can digitally transform healthcare, expand precision medicine, and improve the patient experience. AI and machine learning have recently emerged as powerful tools in healthcare for assisting medical diagnosis.
Artificial intelligence (AI) in medical diagnostics is a tool that has the potential to make healthcare more accessible and affordable by assisting healthcare providers in making accurate and quick treatment decisions for their patients. The accurate diagnosis of a disease takes years of medical training and is a time-consuming process. The use of AI in medical diagnosis has proven to give accurate diagnoses, aid in clinical decisions, and enhance physicians' judgment. Accurate diagnosis is a very important aspect of the healthcare industry.
It is estimated that globally the rate of diagnostic errors is considerably high. According to Southern Medical Association, in the U.S., about 5% of outpatients receive an incorrect diagnosis, with errors being common for complicated life-threatening diseases. According to the World Health Organization (WHO), more than 138 million patients are prone to medical errors yearly in countries with medium and low economic status. These errors include errors in diagnosis, errors in medicine prescriptions and treatments, and the inappropriate use of drugs that causes harm to the patients. While in the U.S., around 12 million people are affected by medical diagnostic errors every year. (Source: Healthline Media).
AI and machine learning have emerged as powerful tools that have the potential to provide more accurate diagnoses and help the physician in clinical decision-making. Several research studies have suggested that AI performs as well as or better than humans at key healthcare tasks, such as diagnosing diseases. Some studies have reported that AI algorithms outperform radiologists at detecting malignant tumors.
The machine learning algorithms can identify patterns by learning them from thousands of examples. Since the availability of healthcare data is increasing, these AI algorithms are getting better at diagnostics comparable to doctors and specialists. However, these algorithms can analyze the data and conclude the diagnosis in a fraction of a second.
The demand for AI in medical imaging is increasing due to its ability to detect the disease earlier and enhance workflows by accelerating reading time and automatically prioritizing urgent cases. AI-based solutions can analyze a vast number of medical images and then quickly and regularly identify patterns, including variations that humans cannot. This can lead to early diagnosis and treatment of many serious diseases, including cancers, which may cut treatment costs by more than 50% (Source: PeerJ Journal). The applications of AI in making diagnoses based on medical imaging are vast and include oncology, cardiology, gastroenterology or hepatology, and neurology, among others. Additionally, in the cases where there is a lack of expert knowledge available, such as in remote or poorly funded medical facilities, there is a great need for AI-based solutions to make accurate diagnoses.
Furthermore, many countries are experiencing a shortage of health professionals, and the gap is continuously widening. The shortage of healthcare professionals has long been an issue of concern in the healthcare industry. Health professionals are essential for expanding healthcare coverage and attaining the right to the highest possible standard of health. According to the WHO estimates, there could be a shortfall of 18 million health workers by 2030, primarily in low- and lower-middle-income countries. However, the demand for healthcare professionals is on the rise. The main factors for rising demand for healthcare professionals are population growth and aging, increasing prevalence of chronic diseases, limited capacity of education programs, and aging and retiring healthcare workforce. The adoption of AI in medical diagnostics aids physicians in making a quick and accurate medical diagnosis. It also helps to reduce the work stress of overworked medical professionals.
Moreover, the outbreak of the COVID-19 pandemic significantly increased the demand for AI-based solutions. The COVID-19 disease mainly affects the lungs of the patients. Hence, cardiothoracic imaging in COVID-19 cases is a common diagnostic practice to identify the severity of the disease. The number of research studies using AI techniques to diagnose COVID-19 rapidly increased in 2020. Many studies were focused on describing the diagnosis of COVID-19 from chest CT images using AI technology. Several studies proved that AI models might be as accurate as experienced radiologists in diagnosing COVID-19. The role of AI in assisting the healthcare sector in fighting the COVID-19 pandemic is evident, and its adoption is expected to increase in the future.
According to Meticulous Research®, the AI in medical diagnostics market is expected to grow at a CAGR of 36.2% to reach $9.38 billion by 2029.
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