The global artificial intelligence (AI) in diagnostics market size was valued at USD 915.41 million in 2022. It is estimated to reach USD 11,596.71 million by 2031, growing at a CAGR of 32.6% during the forecast period (2023–2031).
AI is an intelligent system that connects numerous human intelligence-based capabilities, including reasoning, learning, and problem-solving, to biology, engineering, mathematics, computer science, linguistics, and psychology. Incorporating artificial intelligence (AI) and machine learning techniques into the healthcare sector makes medication research and development more creative, efficient in time and money, and innovative. In addition, artificial intelligence is primarily employed in the medical field to examine the connection between patient outcomes and treatment methods.
AI is utilized in diagnostics to analyze complex medical and imaging data and approximate human cognition. AI programs are used in all medical procedures, including diagnostic procedures, drug research, individualized treatment, and patient monitoring care. AI systems can also be used for alerts and reminders, picture interpretation, information retrieval, and therapeutic planning during medical procedures. Additionally, AI has a wide range of applications in medical diagnostics, including speech analysis for emotional state and psychiatric illnesses, picture analysis for tumor diagnosis, and video detection for gait problems and fall prediction.
The practice of medical diagnostics is rapidly changing with the development and adoption of Artificial Intelligence (AI). Constant improvements in computer processing have enabled AI-based systems to provide accurate and efficient diagnosis and treatment management plans across various specializations. In addition, AI can play a significant role in diagnosis and healthcare, with advancements in computing power, learning algorithms, cloud storage, and the availability of datasets from electronic health records. It can enable radiologists and pathologists to accurately diagnose conditions at an early stage to provide adequate and effective treatment.
Furthermore, AI-based devices collect data from imaging technologies like ultrasound, MRI, CT, and PET. In its first stage, AI automatically segments various imaging data and structures to yield significant analytical value and help save the radiologist's time. Over the next decade, AI-based radiology solutions will likely perform routine tasks such as quantification, segmentation, and pattern recognition before the radiologist's analysis, thereby improving patient care delivery. Therefore, the early detection and classification of diseases drive the market's growth.
AI has an influential impact on chronic disease detection and management. As per the American Hospital Association's article titled Health for Life in March 2018, an estimated 45% of the U.S. population, or 133 million people, suffer from at least one chronic condition. Over 1.7 million people die yearly in the U.S. due to chronic illnesses. In addition, the growing prevalence of chronic diseases is one of the crucial factors expected to boost demand for accurate diagnosis. It is also estimated that by 2025, 49% of the total U.S. population will be affected by chronic conditions. As per the U.S. CDC, many of these conditions are preventable through early diagnosis and adequate treatment plans. An increased number of people suffering from chronic diseases is another key factor anticipated to drive the market over the forecast period.
The AI-based healthcare market includes high procurement costs and requires significant initial capital, followed by upgradation and maintenance costs. The private consumer bears the majority of the costs for creating and implementing AI-based technologies due to limited government expenditure. Procurement of hardware and software solutions to integrate AI into the healthcare setting involves high costs due to the complexity of engineering in the system. In addition, substantial investments are required in digitalization and training programs. Healthcare systems have already made significant capital investments in rolling out electronic health record systems and acquiring and integrating AI solutions in healthcare settings, which is likely an expensive ordeal. Therefore, the abovementioned factors will likely restrain the market's growth.
The artificial intelligence (AI) healthcare market rapidly expands, presenting business owners with numerous unrealized potentials. As per a DataRoot Labs article in September 2020, AI innovation in healthcare has been overwhelming over recent years. In addition, the market is expected to grow from USD 0.95 billion in 2017 to USD 19.25 billion in 2026 at a CAGR of 39.7%. The healthcare space also holds large volumes of data from imaging, genomics, and diagnostics, leading to startups' emergence over recent years.
Furthermore, the increasing number of collaborations is boosting the emergence of AI-based healthcare startups. For example, IBM Watson collaborated with Quest Diagnostics to develop AI Genetic Diagnostic Analysis to analyze genetic data and identify rare secondary leukemia cancers in Japan. In addition, acquisitions of startups by established firms and organizations are likely to boost the entrepreneurship venture space. For example, Merck merged ConnectMed, a telehealth application provider, with its CURAFA point-of-care segment in Kenya to strengthen its portfolio. Venture capital investment in AI-based healthcare companies is providing strong evidence of the expected impact of AI on healthcare. These factors are expected to offer tremendous opportunities for the market's growth.
The global artificial intelligence (AI) in diagnostics market is segmented by component and diagnosis type.
Based on components, the global artificial intelligence (AI) in diagnostics market is divided into software, hardware, and services.
The software segment is responsible for the largest market share and is anticipated to grow at a CAGR of 33.6% over the forecast period. Increasing demand for AI-powered and cloud-based augmented diagnostics solutions that helps in delivering better diagnostic precision while interpreting patient medical images is one of the key factors driving the segment. Moreover, the COVID-19 pandemic, coupled with the introduction of advanced AI software in diagnostics, involves combining multiple data sources, such as genomics and proteomics, MRI, CT, and patient data that aids in successfully diagnosing disease and assessing its progression is also expected to drive the market. For instance, in February 2018, John Snow Labs launched Natural Language Processing (NLP) library with healthcare-specific deep learning models that aid developers in creating software applications that understand medical texts. This allows healthcare professionals to analyze and determine patients at higher risk, match patients to clinical trials, alert caregivers about patient safety, automate clinical coding and billing, and make significant clinical recommendations that contribute to the growth of AI software used in healthcare.
The growth of the services segment can be majorly attributed to the rising need for integration and implementation of AI solutions, support and maintenance, training, and education. In addition, the rising adoption of AI platforms has also driven the demand for support and maintenance services to keep the devices' functionality. This, in turn, has led to a significant rise in demand for the services segment. Furthermore, an increase in the need for uninterrupted data flow between devices and people to boost the security and efficiency of medical devices and enhance informed decision-making in real time are some of the factors expected to drive the services segment. Moreover, growing awareness and increasing adoption of cloud-based technologies, application programming interfaces, and remote device management services among healthcare professionals are among the key factors responsible for the growth of the services segment.
Based on diagnosis type, the global artificial intelligence (AI) in diagnostics market is segmented into cardiology, oncology, pathology, radiology, chest and lung, neurology, and others.
The neurology segment owns the highest market share and is expected to exhibit a CAGR of 31.7% during the forecast period. The rise in the senior population and the increase in the prevalence of various neurological diseases, such as epilepsy, Alzheimer's disease, and Parkinson's disease, drive demand for effective diagnosis, positively impacting the market growth. According to United Nations World Ageing Population 2017 report, the number of people aged 60 and above will double by 2050, rising from 962 million in 2017 to 2.1 billion by 2050. In addition, the launch of many products over the past two years indicates the growing adoption of AI in the healthcare sector. For instance, in December 2018, LabIndia Healthcare and MedAchievers announced the launch of an AI-based open orthopedic surgery simulator for training neurology and orthopedic surgeons. This AI-based open surgery simulator provides an ideal environment for doctors to observe results and check and improve surgical performance.
AI in radiology has helped reduce turnaround time and enhance patient safety, thus addressing the need for onsite radiologists. The radiology segment is expected to record the fastest growth rate over the forecast period. Its high growth rate can be attributed to the adoption of AI-based healthcare solutions in diagnostics. The increasing integration of solutions in the early detection and classification of diseases by healthcare facilities is likely to drive the growth of this segment. In addition, with access to smart electronic health reports and radiological examination data, AI and machine learning systems can detect chronic diseases early so that adequate care can be received beforehand. The increasing use of these solutions in diagnostic departments of healthcare facilities to capture data and provide accurate and precise outcomes is likely to propel the segment over the forecast period.
Based on region, the global artificial intelligence (AI) in diagnostics market is bifurcated into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa.
North America is the most significant global artificial intelligence (AI) in diagnostics market shareholder and is anticipated to exhibit a CAGR of 32.8% during the forecast period. Increasing adoption of Artificial Intelligence (AI) in disease identification and diagnosis and investment in AI healthcare startups are factors expected to drive North America's AI in the diagnostics market. In addition, the growing demand for reducing diagnostic costs, improving patient care, and reducing machine downtime further accelerates AI usage in diagnostics. According to Health IT Analytics in May 2017, Case Western Reserve University researchers used a deep learning network, a subset of AI, to identify breast cancer in pathology images with 100% accuracy.
Furthermore, the COVID-19 pandemic, coupled with growing government initiatives, increasing mergers and acquisitions, portfolio expansion, and collaborations to promote AI implementation in healthcare, accelerate its adoption in diagnostics, thereby contributing to market growth. For instance, in August 2020, Digital Diagnostics Inc., formerly known as IDx, acquired 3Derm Systems Inc. The acquisition aimed to include telemedicine capabilities for dermatology and 3DermTriage and to prepare its autonomous AI skin cancer diagnostic system, 3DermSpot, for FDA authorization.
Europe is projected to exhibit a CAGR of 32.5% over the forecast period. The healthcare industry in Europe is under pressure, owing to various key factors such as rising costs, increasing prevalence of chronic conditions, rapidly aging population, growing demand for treatments, and stagnating or shrinking healthcare workforce threatening its sustainability. The industry also needs help with structural inefficiencies in certain European countries. The move to value-based healthcare is expected to strengthen the demand for better patient outcomes at a more sustainable cost. Incorporating AI into innovative medical technologies can address pressing healthcare issues. In addition, many AI applications in healthcare are already in operation or awaiting deployment, which can contribute to earlier disease detection, more accurate diagnosis, identification of new observations or patterns in human physiology, and development of personalized diagnostics and therapeutics. In April 2019, The EU introduced healthcare guidelines for developing ethical AI applications for companies and governments. Such factors are expected to drive regional market growth.
Asia-Pacific is anticipated to register significant growth over the forecast period. This growth is seen through the development and innovations in entrepreneurship startups established in Asia-Pacific countries. Government initiatives, private funding, and incubations for newly launched startups to receive the right direction in innovating AI-based solutions will likely drive the market. There has also been a rise in venture capitalist investments and cooperation with these company initiatives, which can aid in creating fresh solutions and consequently stimulate market expansion. In April 2018, China's Ministry of Education introduced an Action Plan, AI innovation for Colleges and Universities, to lead AI training and innovation by 2030. This plan was to create 100 AI-specialized programs by 2020 for specific domains, such as AI in healthcare, driving the market's growth.
Latin America is expected to be a potentially lucrative region for AI in the diagnostics market, owing to the ongoing COVID-19 pandemic, shortage of skilled staff, and government readiness for adopting newer technology. The increasing scope of digitization, IT infrastructure development, technological advancements to enhance the quality of patient care, and reductions in healthcare expenses are expected to drive the market in the region. In 2019, Brazilian Minister Marcos Pontes created eight AI laboratories with a specific focus on partnership with public research support and financing entities. Four of the eight laboratories were defined as smart cities, health, industry 4.0, and agribusiness.
Increasing chronic ailments, such as respiratory disorders and heart diseases, and the growing geriatric population is boosting the demand for healthcare facilities in the Middle East and Africa. Moreover, the COVID-19 pandemic and increased mergers and acquisitions, investments, and partnerships are further growing the overall market. For instance, in January 2020, Oxipit announced its collaboration with Healthcare Konnect to bring the ChestEye AI imaging suite to healthcare institutions in Nigeria. The partnership aimed to introduce Vanguard AI diagnostic capabilities and improve the detection capabilities of 75 pathologies.
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