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.
| Report Attribute | Specifications |
| Market Size Value In 2022 | USD 285.90 Million |
| Revenue Forecast In 2031 | USD 1371.16 Million |
| Growth Rate CAGR | CAGR of 19.2 % from 2023 to 2031 |
| Quantitative Units | Representation of revenue in US$ Million and CAGR from 2023 to 2031 |
| Historic Year | 2019 to 2022 |
| Forecast Year | 2023-2031 |
| Report Coverage | The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
| Segments Covered | By Surgery Type, By Cancer Type, By Application, By Component, By End-User |
| Regional Scope | North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
| 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 |
| 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 |
| Customization Scope | Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
| 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
This study employed a multi-step, mixed-method research approach that integrates:
This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.
Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.
Secondary data for the market study was gathered from multiple credible sources, including:
These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.
Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.
Primary interviews for this study involved:
Interviews were conducted via:
Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.
All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.
The data validation process included:
This ensured that the dataset used for modelling was clean, robust, and reliable.
The bottom-up approach involved aggregating segment-level data, such as:
This method was primarily used when detailed micro-level market data were available.
The top-down approach used macro-level indicators:
This approach was used for segments where granular data were limited or inconsistent.
To ensure accuracy, a triangulated hybrid model was used. This included:
This multi-angle validation yielded the final market size.
Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.
Given inherent uncertainties, three scenarios were constructed:
Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.