Artificial Intelligence in Diagnostics Market is expected to grow at a CAGR of 26.1% over the forecast period.
The COVID-19 pandemic has had a significant impact on the healthcare system, particularly diagnostics. The lockdown measures worldwide resulted in decreased public mobility and impacted the diagnostic industry. Moreover, the COVID-19 pandemic not only affected the global economy but also showed a huge impact on the functioning of general hospital care for non-COVID-19 patients in hospitals across the globe. According to an article appearing in the JAMA Network in August 2020, there has been a significant decline in breast cancer diagnoses (by as much as 51.8 percent) in the United States from March 1, 2020, to April 18, 2020. This is expected to have a slightly negative impact on Artificial Intelligence in diagnostics as their demand has reduced significantly.
On the other hand, as the COVID-19 pandemic spread, artificial intelligence became a vital part in the fight against it. AI tools were employed to handle the pandemic's depth and complexity, from diagnosis to drug development, disease transmission prediction, and population monitoring and surveillance. A study titled, "The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic" published in the Journal of "Nature Public Health Emergency Collection" in April 2021, proposed a temporal step method, which includes presenting recent research investigations, examining how AI observes and acts on society and the health-care system, and reporting various data types. Hence, AI research has shown effectiveness mainly in a restricted range of activities, such as image diagnostics.
Furthermore, according to the "Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment" published in the Journal of " IEEE Public Health Emergency Collection" in June 2020, the rise in popularity of AI applications in clinical settings can contribute to a reduction of unnecessary deletions while also increasing productivity and efficiency in research involving large samples and requiring better levels of accuracy in prediction and diagnosis. Medical imaging and image processing techniques could benefit from AI. For example, image-based medical diagnosis, which can provide a quick and accurate diagnosis of COVID-19, is one field that can benefit from AI's beneficial input.
Moreover, as per the "Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis" published in September 2020, researchers have demonstrated the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images using a commercial platform that is readily available. While this technology has a wide range of applications in radiology, researchers have been particularly interested in its potential impact on future global health crises like COVID-19. The findings have implications for patient screening and triage, early diagnosis, disease progression tracking, and identifying patients who are at higher risk of morbidity and mortality. As per the research findings, artificial intelligence (AI) will likely transform medical practice in the future. Therefore, it is expected to have a positive impact on the target market during the forecast period.
The incorporation of artificial intelligence in the devices may improve the diagnosis, which in turn is expected to aid the overall target market growth during the forecast period. For instance, the Journal of the American Medical Association article titled 'An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study' published in December 2021 reported that an Artificial Intelligence algorithm was associated with improved detection of pulmonary nodules on chest radiographs compared with unaided interpretation for different levels of detection difficulty and readers with different experience. The research articles show that artificial intelligence may be a promising technology for medical imaging and also boost the market's growth.
However, the lack of a skilled AI workforce and ambiguous regulatory guidelines for medical software is expected to restrain the market growth.
The X-rays segment is expected to dominate the target market growth during the forecast period. Radiologists can use artificial intelligence (AI) to improve the quality of service and increase the value of radiography in patient care and public health. Since X-rays are the most common imaging tests performed in most radiology departments, the potential for AI to aid with the triage and interpretation of traditional radiographs (X-ray images) is particularly significant. The incorporation of AI in X-rays enhances its efficiency, accuracy, ease of access, and workflow reducing time and increasing quality and patient safety. This benefit is expected to increase the demand for AI in X-rays, in turn, it is expected to aid the segment growth during the forecast period.
Additionally, the Imaging Informatics and Artificial Intelligence Journal's article titled 'Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation' in November 2020 concluded that the simulations demonstrate that smart worklist prioritization by Artificial Intelligence can reduce the average Report Turnaround Times (RTAT) for critical findings in chest x-rays. Such articles demonstrate the smooth workflow due to the advanced technology driving the segment growth.
Furthermore, rise in product launches by the industry players is anticipated to drive the segment growth. For instance, in June 2020, Siemens Healthineers introduced Ysio X.pree - an intelligent X-ray system with integrated AI for optimizing the daily routine of image acquisition in radiography.
Thus, owing to the abovementioned factors, it is expected to drive the diagnostic imaging segment growth over the forecast period.
Artificial intelligence in the diagnostics market in North America is being driven by the increasing use of advanced technology in healthcare systems and the rising burden of chronic diseases in the country. For instance, according to GLOBOCAN 2020, 2,281,658 new cancer cases were diagnosed in the United States in 2020, with 612,390 fatalities. The increased prevalence of chronic diseases increases the demand for accurate diagnosis and treatment. As a result, the studied market in the country is expected to grow over the coming years.
Furthermore, according to statistics published by the Government of Canada, released in November 2021, in 2021, about 229,200 Canadians were expected to diagnose with cancer, and 84,600 will die from cancer. Lung, breast, colorectal, and prostate cancers are expected to remain the most commonly diagnosed cancers, accounting for 46% of all diagnoses in 2021. According to the same source, breast cancer affects one out of every eight women at some time in their lives. Thus, as the number of cancer cases rises, so does the demand for early diagnosis, hence, driving demand for AI in Diagnostics over the projection period.
Several market players are engaged in the implementation of strategic initiatives, thereby contributing to segment growth. For instance, in December 2021, Roche introduced three artificial intelligence (AI)-based, deep learning image analysis Research Use Only (RUO) algorithms developed for breast cancer.
As a result, all of the aforementioned reasons are likely to contribute to this segment's strong growth over the forecast period.
The Artificial Intelligence in Diagnostics Market is moderately competitive and consists of several major players. Some of the companies which are currently dominating the market are Siemens Healthineers, Nanox Imaging LTD (Zebra Medical Vision, Inc.), Riverain Technologies, Vuno, Inc., Aidoc, Neural Analytics, Imagen Technologies, Digital Diagnostics, Inc., GE Healthcare, AliveCor Inc., Enlitic, and InformAI.
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The COVID-19 pandemic has had a significant impact on the healthcare system, particularly diagnostics. The lockdown measures worldwide resulted in decreased public mobility and impacted the diagnostic industry. Moreover, the COVID-19 pandemic not only affected the global economy but also showed a huge impact on the functioning of general hospital care for non-COVID-19 patients in hospitals across the globe. According to an article appearing in the JAMA Network in August 2020, there has been a significant decline in breast cancer diagnoses (by as much as 51.8 percent) in the United States from March 1, 2020, to April 18, 2020. This is expected to have a slightly negative impact on Artificial Intelligence in diagnostics as their demand has reduced significantly.
On the other hand, as the COVID-19 pandemic spread, artificial intelligence became a vital part in the fight against it. AI tools were employed to handle the pandemic's depth and complexity, from diagnosis to drug development, disease transmission prediction, and population monitoring and surveillance. A study titled, "The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic" published in the Journal of "Nature Public Health Emergency Collection" in April 2021, proposed a temporal step method, which includes presenting recent research investigations, examining how AI observes and acts on society and the health-care system, and reporting various data types. Hence, AI research has shown effectiveness mainly in a restricted range of activities, such as image diagnostics.
Furthermore, according to the "Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment" published in the Journal of " IEEE Public Health Emergency Collection" in June 2020, the rise in popularity of AI applications in clinical settings can contribute to a reduction of unnecessary deletions while also increasing productivity and efficiency in research involving large samples and requiring better levels of accuracy in prediction and diagnosis. Medical imaging and image processing techniques could benefit from AI. For example, image-based medical diagnosis, which can provide a quick and accurate diagnosis of COVID-19, is one field that can benefit from AI's beneficial input.
Moreover, as per the "Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis" published in September 2020, researchers have demonstrated the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images using a commercial platform that is readily available. While this technology has a wide range of applications in radiology, researchers have been particularly interested in its potential impact on future global health crises like COVID-19. The findings have implications for patient screening and triage, early diagnosis, disease progression tracking, and identifying patients who are at higher risk of morbidity and mortality. As per the research findings, artificial intelligence (AI) will likely transform medical practice in the future. Therefore, it is expected to have a positive impact on the target market during the forecast period.
The incorporation of artificial intelligence in the devices may improve the diagnosis, which in turn is expected to aid the overall target market growth during the forecast period. For instance, the Journal of the American Medical Association article titled 'An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study' published in December 2021 reported that an Artificial Intelligence algorithm was associated with improved detection of pulmonary nodules on chest radiographs compared with unaided interpretation for different levels of detection difficulty and readers with different experience. The research articles show that artificial intelligence may be a promising technology for medical imaging and also boost the market's growth.
However, the lack of a skilled AI workforce and ambiguous regulatory guidelines for medical software is expected to restrain the market growth.
Key Market Trends
X-rays Segment is Expected to Dominate the Market
The X-rays segment is expected to dominate the target market growth during the forecast period. Radiologists can use artificial intelligence (AI) to improve the quality of service and increase the value of radiography in patient care and public health. Since X-rays are the most common imaging tests performed in most radiology departments, the potential for AI to aid with the triage and interpretation of traditional radiographs (X-ray images) is particularly significant. The incorporation of AI in X-rays enhances its efficiency, accuracy, ease of access, and workflow reducing time and increasing quality and patient safety. This benefit is expected to increase the demand for AI in X-rays, in turn, it is expected to aid the segment growth during the forecast period.
Additionally, the Imaging Informatics and Artificial Intelligence Journal's article titled 'Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation' in November 2020 concluded that the simulations demonstrate that smart worklist prioritization by Artificial Intelligence can reduce the average Report Turnaround Times (RTAT) for critical findings in chest x-rays. Such articles demonstrate the smooth workflow due to the advanced technology driving the segment growth.
Furthermore, rise in product launches by the industry players is anticipated to drive the segment growth. For instance, in June 2020, Siemens Healthineers introduced Ysio X.pree - an intelligent X-ray system with integrated AI for optimizing the daily routine of image acquisition in radiography.
Thus, owing to the abovementioned factors, it is expected to drive the diagnostic imaging segment growth over the forecast period.
North America Dominates the Market and Expected to do Same in the Forecast Period
Artificial intelligence in the diagnostics market in North America is being driven by the increasing use of advanced technology in healthcare systems and the rising burden of chronic diseases in the country. For instance, according to GLOBOCAN 2020, 2,281,658 new cancer cases were diagnosed in the United States in 2020, with 612,390 fatalities. The increased prevalence of chronic diseases increases the demand for accurate diagnosis and treatment. As a result, the studied market in the country is expected to grow over the coming years.
Furthermore, according to statistics published by the Government of Canada, released in November 2021, in 2021, about 229,200 Canadians were expected to diagnose with cancer, and 84,600 will die from cancer. Lung, breast, colorectal, and prostate cancers are expected to remain the most commonly diagnosed cancers, accounting for 46% of all diagnoses in 2021. According to the same source, breast cancer affects one out of every eight women at some time in their lives. Thus, as the number of cancer cases rises, so does the demand for early diagnosis, hence, driving demand for AI in Diagnostics over the projection period.
Several market players are engaged in the implementation of strategic initiatives, thereby contributing to segment growth. For instance, in December 2021, Roche introduced three artificial intelligence (AI)-based, deep learning image analysis Research Use Only (RUO) algorithms developed for breast cancer.
As a result, all of the aforementioned reasons are likely to contribute to this segment's strong growth over the forecast period.
Competitive Landscape
The Artificial Intelligence in Diagnostics Market is moderately competitive and consists of several major players. Some of the companies which are currently dominating the market are Siemens Healthineers, Nanox Imaging LTD (Zebra Medical Vision, Inc.), Riverain Technologies, Vuno, Inc., Aidoc, Neural Analytics, Imagen Technologies, Digital Diagnostics, Inc., GE Healthcare, AliveCor Inc., Enlitic, and InformAI.
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Table of Contents
1 INTRODUCTION
4 MARKET DYNAMICS
5 MARKET SEGMENTATION (Market Size by Value - USD million)
6 COMPETITIVE LANDSCAPE
Companies Mentioned
A selection of companies mentioned in this report includes:
- Siemens Healthineers
- Nanox Imaging LTD (Zebra Medical Vision, Inc.)
- Riverain Technologies
- Vuno, Inc.
- Aidoc
- Neural Analytics
- Imagen Technologies
- Digital Diagnostics, Inc.
- GE Healthcare
- AliveCor Inc.
- Enlitic
- InformAI
Methodology
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