The Artificial Intelligence in Cancer Diagnosis and Therapy Market Size is valued at 285.90 Million in 2022 and is predicted to reach 1371.16 Million by the year 2031 at a 19.2 % CAGR during the forecast period for 2023-2031.
The realm of health is just one of many areas of human life where artificial intelligence (AI) has made its way. Detecting cancer may provide the most complex and selfless task for AI in the field of medicine. AI would be beneficial in dealing with the tiresome, repetitive, and time-consuming task of lesion detection, eliminating the potential for human error, and reducing expenses and time. The significance of this would be enormous for cancer screening programmes. AI systems can identify information from digital images from radiology and pathology that is invisible to the human eye (radiomics and pathomics). A better knowledge of malignancies will result from the correlation of radiomics and patronymics with clinico-demographic-therapy-morbidity-mortality profiles. It has been discovered that particular imaging abnormalities are linked to particular gene-determined molecular pathways implicated in cancer aetiology (radiogenomics). All of these advancements would contribute to the personalization of oncologic care as well as the creation of new imaging biomarkers. Cancer screening (identification of lesions), classification and grading of tumours, clinical decision-making, and prognostication are the main uses of AI algorithms in oncoimaging and oncopathology. AI cannot, however, be a failsafe panacea or take the place of humans in all situations.
The Artificial Intelligence in Cancer Diagnosis and Therapy market is segmented on the basis of surgery type, cancer type, and end-use. Based on surgery type, the market is segmented as Radiotherapy, Chemotherapy, Immunotherapy, Precision Therapy, Phototherapy, Gene Therapy, and Sonodynamic Therapy. By cancer type, the market is segmented into Breast Cancer, Lung Cancer, Melanoma Cancer, Colorectal Cancer, Prostate Cancer, and Others. By end-use, the market is segmented into Hospitals, Cancer Research Centre, and Diagnostic Labs.
In 2021, the immunotherapy market accounted for a sizeable portion of total revenue. A key development in the fight against cancer is immunotherapy. Additionally, the integration of AI improves the likelihood that cancer immunotherapy will be effective by forecasting therapeutic impact based on the development of immunotherapy prediction scores like Immunocore and immunophenoscore. In order to forecast how patients would react to Immune Checkpoint Blockade (ICB) medications, these two grading systems were created. For cancer subtypes that are indistinguishable, combining AI-based diagnostic algorithms with clinical interpretations may improve diagnostic precision. The accuracy of AI technology in identifying Major Histocompatibility Complex (MHC) patterns linked to immunotherapy response is 91.66 %. Importantly, AI may be used to standardize exams across institutions, as opposed to relying on doctors' frequently arbitrary interpretations.
In 2021, the prostate cancer market contributed a modest portion of total revenue. The most prevalent non-skin cancer in men and the second greatest cause of cancer-related death is prostate cancer. Additionally, it is projected that this illness will have a lifetime impact on one in six American boys. Healthcare-related AI and machine learning are two newly emerging research areas that have recently received a lot of attention. In addition, artificial neural networks, which employ statistical models partly based on and inspired by organic brain networks, are frequently used in AI. They have the capacity to simultaneously represent and understand nonlinear interactions between inputs and outputs. Overall, it has been demonstrated that the use of AI in prostate cancer has been beneficial in assisting standardized pathological grading in evaluating the classification and treatment of prostate cancer. Additionally, using image-based activities like histopathology, MRI, and biomarker identification, AI has the capacity to automate the characterization and severity evaluation of prostate cancer.
The market for AI in cancer diagnostics grew significantly in line with North America's growing preference for AI technology in the healthcare industry. The majority of newly established businesses in the same market have a respectable foothold in the area. Within minutes, a Microsoft system's Inner Eyes showed conclusive evidence of imaging and analyzing prostate cancer. In the market for cancer diagnostics as well, North America is anticipated to dominate. In Canada, 45 % of men and 43 % of women will develop cancer during their lifetimes, according to Canadian Cancer Statistics. However, the nation is actively implementing AI across the healthcare sector to fight this issue.
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Report Attribute |
Specifications |
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Market Size Value In 2022 |
USD 285.90 Million |
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Revenue Forecast In 2031 |
USD 1371.16 Million |
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Growth Rate CAGR |
CAGR of 19.2 % from 2023 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2023 to 2031 |
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Historic Year |
2019 to 2022 |
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Forecast Year |
2023-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Surgery Type, By Cancer Type, By Application, By Component, By End-User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia |
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Competitive Landscape |
Ekso Bionics Holdings Inc., Hocoma AG, MindMaze, Neuro Rehab VR, ReWalk Robotics, Eodyne, reHaptix GmbH, Neofect, Oxford VR, Euleria, Barron Associates, Virtual Therapy Solutions, LLC, Recovery Tech, Inc., ICAROS GmbH, and Others |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
By Surgery Type-
By Cancer Type-
By Component-
By Application-
By End-Use-
By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
Rest of Middle East and Africa
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
