Computer Vision in Healthcare Market Outlook - 2030
Computer vision is designed to recognize, understand images and data to execute actions that only humans were once thought to be capable of performing. As AI continues to grow, it is expanding the frontiers of healthcare, augmenting diagnostic and treatment tools, and helping healthcare professionals prognosticate diseases more effectively. This will undoubtedly improve patient care outcomes and reduce avoidable delays in the patient care continuum.
These are the following application of computer vision in healthcare include, cancer screening, disease diagnostic and surgical assisted technology.
Artificial Intelligence is revolutionizing everything - commerce, social interactions, and even healthcare. With more machine learning models being developed, Computer Vision will further transform healthcare, creating a more efficient diagnostic and treatment system to improve patient care outcomes.
Covid-19 Scenario analysis:
The global outbreak of COVID-19 leads to an ongoing downturn of the healthcare market. Apart from communities, COVID-19 was equally disastrous for major world economies, especially the healthcare sector. Prominent stakeholders are continuing to adapt their strategies to the rapidly changing situation. COVID-19 is projected to have significant long-term impacts on the healthcare industry. Countries and major players would have to undertake critical healthcare changes until the crisis takes a back seat.
Technological progress, cost containment, and increased access are projected to be an integral part of healthcare reforms in the near future. Digital health and telehealth have taken a front seat in the ongoing outbreak. COVID-19 re-emphasized the importance of remote diagnosis, care, and consultation. Over the past few years, regulatory and behavioral barriers have slowed Telehealth growth. However, since many healthcare providers are currently working on video conferencing and telephone calls, the segment is anticipated to experience growth over the next two years. The social distancing measures also mandated online consultation of patients with moderate symptoms. In addition, it greatly reduced the burden on hospitals already swamped by counts of COVID-19 patients. Medical IoT devices that live at home with patients are now being used for optimizing outpatient treatment and minimizing repeat visits, and these devices can be further used in a crisis situation. The pandemic led to severe resource constraints. This is expected to result in the development of competitive pricing and value-based pricing models, which boosts the growth of the computer vision in healthcare market
Artificial Intelligence has emerged as a powerful tool in the time to fight against Covid-19. The technology is used to train computers to leverage big data-enabled models for pattern recognition, interpretation, and prediction using Machine Learning, NLP and Computer Vision. China’s Zhongnan Hospital utilizes an AI-powered CT scan interpreter to identify Covid-19 when radiologists aren’t available. Moreover, Wuhan Wuchang Hospital in the country has also developed a smart field hospital staffed largely by robots, which deliver medicine and food to patients, limiting physician exposure to the virus. These applications can be effective to diagnose, envision, and treat Covid-19 disease, and they can also assist in managing socio-economic impacts. Since the pandemic spreads quickly, there has been a rush to explore and deploy AI to cure and address the soaring demand of patient treatment infected by Coronavirus. Besides, many companies around the world have now announced a number of AI-enabled computer vision systems to detect Covid-19 on chest CT or X-ray scans. These deep learning tools are already used in hospitals to screen mild cases, triage new infections, and keep an eye on advancing disease. Hence computer vision in healthcare is booming during this pandemic and increasing demand for AI will show growth in market.
Top impacting factors: Market Scenario Analysis, Trends, Drivers and Impact analysis:
Drivers:
Growth in this market is driven by the increasing demand for computer vision systems in the healthcare industry, government initiatives to increase adoption of AI-based technologies, big data in healthcare, and the use of computer vision in precision medicine.
Precise Diagnoses on increased number of health condition:
Computer vision systems offer precise diagnoses minimizing false positives. This technology can potentially obliterate the requirement for redundant surgical procedures and expensive therapies. Computer vision algorithms trained using a huge amount of training data can detect the slightest presence of a condition which may typically be missed out by human doctors because of their sensory limitations. The use of computer vision in healthcare diagnosis can provide significantly high levels of precision which may in coming days go up to 100 percent.
Fast Detection of Illness:
There are most fatal illnesses that need to be diagnosed in their early stages, such as cancer. Computer vision enables the detection of early symptoms with high certainty owing to its finely tuned pattern-recognition capability. This can be useful in timely treatment and saving countless lives for the long term.
Heightened Medical Process and Precision
The use of computer vision in healthcare can considerably lessen the time doctors usually take in analysing reports and images. It frees and offers them more time to spend with patients and provide personalized and constructive advice. By enhancing the quality of physician-patient interactions, it can also assist medical professionals to give consultation to more and more patients. The use of computer vision in healthcare supports caregivers to deliver efficient and accurate healthcare services through its life-saving applications.
Need of Medical Imaging
For the last decades, computer-supported medical imaging application has been a trustworthy help for physicians. It doesn’t only create and analyse images, but also becomes an assistant and helps doctors with their interpretation. The application is used to read and convert 2D scan images into interactive 3D models that enable medical professionals to gain a detailed understanding of a patient’s health condition.
Need for Health Monitoring
By leveraging computer vision technology doctors can analyse health and fitness metrics to assist patients to make faster and better medical decisions. Today, it is being utilized by healthcare centres to measure the blood lost during surgeries, majorly during C-section procedures. This can assist in taking emergency measures if the quantity of blood lost reaches the last stage. Additionally, the technology can also be leveraged to measure the body fat percentage of people using images taken from regular cameras.
Nuclear Medicine Diagnoses market
As a section of clinical medicine, nuclear medicine deals with the use of radionuclide pharmaceuticals in diagnosis. Sometimes computer vision techniques of remote radiation therapy are also referred to nuclear medicine. In diagnostics, it mainly utilizes single-photon emission computed tomography and positron emission tomography.
Restraints:
Reluctance among medical practitioners to adopt AI-based technologies, and lack of awareness and technical knowledge are expected to restrain market growth to a certain extent. Currently, there exists one big problem in healthcare computer vision. Also, Deep learning models tend to not work well on new data (different from those they were trained on). So, there is still a whole lot to be done in the field.
Regional analysis:
There are many governments and hospital systems around the world using AI-driven sensors to support triage in sophisticated ways. In this way, Chinese technology giant Baidu has built a no-contact infrared sensor system that can quickly recognize individuals with a fever, even in crowds. In the same way, Tampa General Hospital in Florida has deployed an AI system, in association with Care.ai, at its entrances to capture individuals with potential symptoms of Covid-19. By positioning cameras at entrances, the technology escorts a facial thermal scan and distinguishes other symptoms, such as sweat and discoloration, to thwart visitors with fever.
Key benefits of the report:
- This study presents the analytical depiction of the global computer vision in healthcare industry along with the current trends and future estimations to determine the imminent investment pockets.
- The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the global computer vision in healthcare market share.
- The current market is quantitatively analyzed to highlight the global computer vision in healthcare market growth scenario.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
- The report provides a detailed global computer vision in healthcare market analysis based on competitive intensity and how the competition will take shape in coming years.
Questions answered in the Computer vision in healthcare Market research report:
- What are the leading market players active in the computer vision in healthcare market?
- What the current trends will influence the market in the next few years?
- What are the driving factors, restraints, and opportunities in the market?
- What are the projections for the future that would help in taking further strategic steps?
Computer Vision in Healthcare Market Report Highlights
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 Key Market Players | Arterys, AiCure, Xilinx Inc., Google, IBM, Intel Corporation, Basler AG, NVIDIA Corporation, iCAD Inc., Microsoft |
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