Artificial Intelligence (AI) in Inflammatory Bowel Disease Market Size, Growth, Demand, Trends, Report By 2032

The artificial intelligence (AI) in inflammatory bowel disease market is growing at a faster pace with substantial CAGR over the last few years and is estimated that the market will grow significantly between 2023 and 2032, According to Precedence Research.


Ottawa, Dec. 15, 2023 (GLOBE NEWSWIRE) -- The global artificial intelligence (AI) in inflammatory bowel disease market is expected to expand at a remarkable CAGR during the forecast period 2023 to 2032.

The rising prevalence of ulcerative colitis and Crohn's disease is expected to supplement the growth of the inflammatory bowel disease industry in the upcoming years. North America dominates the global market market.

The inflammatory bowel disease (IBD) market is quickly changing as a result of artificial intelligence (AI). In a variety of ways, AI-powered technologies have the potential to enhance the detection, treatment, and management of IBD. Furthermore, AI is being used to develop novel devices for monitoring and managing IBD. AI-powered apps, for example, can be utilized to monitor patient symptoms, medication adherence, and various other important parameters. This data is then applicable to identify patients who are likely to experience flare-ups or other consequences.

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Key Insights:

  • By Technology, the machine learning segment is estimated to expand at a CAGR fastest during the projected period.
  • By End User, the consumer healthcare segment is projected to grow at the fastest CAGR over the projected period.
  • By IBD Type, the ulcerative colitis segment had the largest market share.
  • By Application, the diagnosis segment has held the biggest revenue share in 2022.

Growth Factors

The rising prevalence of ulcerative colitis and Crohn's disease is expected to supplement the growth of inflammatory bowel disease industry in the upcoming years. Computer-aided image assessment has the potential to improve the way of interpreting diagnostic imaging to determine disease activity. As a result, the use of AI-assisted imagery is projected to grow as technology advances. 

Deployment of artificial intelligence can help healthcare systems reduce costs by optimizing resource allocation, reducing unnecessary tests, and preventing hospital readmissions. Additionally, AI can integrate and analyze vast amounts of diverse healthcare data, enabling better insights and decision-making. Certainly, these growth factors are observed to promote the market's growth during the forecast period.  

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Report Highlights:

  • By Technology, the computer vision segment is expected to witness a remarkable rate of growth during the forecast period. AI-powered computer vision can provide consistent results, reducing interobserver variability in diagnosis. Computer vision is capable of processing a large number of images quickly, helping doctors with accurate diagnosis and treatment planning.
  • By IBD type, the Crohn's disease segment is anticipated to grow at a fastest rate over the projected period. AI is being utilized for developing new CD diagnostic tools, like AI-powered devices that can analyze endoscopic pictures to detect inflammation and other symptoms of disease activity. This can help to enhance diagnosis accuracy and efficiency. AI is also being used to create new CD treatment planning tools. AI-powered systems, for example, can be used to analyze massive quantities of patient data, such as medical history, treatment history, and genetic makeup, in order to uncover patterns and relationships. This data can then be utilized to develop personalized treatment regimens that are suited to each patient's specific needs.
  • By Application, the monitoring segment is expected to grow at a significant rate. AI can better assess disease activity in IBD patients by using medical data. In a study of 187 UC patients, a proprietary ML algorithm, referred to as a computer-aided diagnostic (CAD) tool, was used as input to detect chronic histological inflammation and disease activity using endocytoscopy images. AI models can use a variety of data sources, such as electronic health records, patient-reported outcomes, as well as genetic information, to forecast disease progression, treatment response, and probable consequences in IBD patients. This data can assist clinicians in personalising treatment programmes and optimising patient management tactics.

On the other hand, the prognosis segment is observed to witness a notable rate of growth during the forecast period. Several ML techniques have been shown to improve the prognosis of IBD patients. To begin, an RF model was built from the longitudinal electronic medical records of 20,368 IBD patients to predict IBD-related hospitalization and corticosteroid use. This model predicted the number of IBD-related hospitalizations and outpatient corticosteroid prescriptions using IBD-related patient data such as age and longitudinal laboratory data such as serum albumin, CRP, and CBC levels.

  • By End-user, the pharmaceutical companies segment is expected to generate a significant revenue throughout the forecast period. Pharmaceutical companies often have significant financial resources and access to top-tier scientists, researchers and data analysts, enabling them to develop and deploy advanced technologies for IBD research.

Regional Snapshot

North America carries a dominating share of artificial intelligence in inflammatory bowel disease market owing to the rising cases of IBD in the region and rapid adoption of advanced technologies in the healthcare sector. Over 700,000 Americans have IBD, according to the Crohn's and Colitis Foundation. North American healthcare providers are rapidly implementing AI-powered technologies to improve care quality and efficiency.

The United States is North America's largest market for AI in IBD. IBM has created Watson for IBD in the United States, an AI-powered system that can analyse enormous amounts of patient data to uncover patterns and relationships. This information can then be used to develop personalized treatment plans for patients with IBD. Furthermore, in 2022, researchers at the University of California, San Francisco developed an AI-powered system that can predict the risk of relapse in patients with Crohn's disease. The system was able to predict relapse with an accuracy of 80%.

Europe is observed to witness a significant growth rate in the market during the forecast period. A number of factors are driving market expansion, including the rising incidence of IBD in Europe, the increased desire for personalized treatment, and the region's expanding usage of AI in healthcare. In the United Kingdom, the company Huma developed a patient-facing app that employs artificial intelligence to detect and monitor symptoms, adherence to medications, and other important variables in IBD patients. This data can then be used to identify patients who are likely to experience flare-ups or other consequences. Furthermore, Google AI is collaborating with a number of European healthcare organizations to create AI-powered treatments for IBD. Google AI, for example, is collaborating with the University of Cambridge to create an AI-powered system to increase the accuracy of IBD diagnosis.

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Scope of         

Report CoverageDetails
Largest MarketNorth America
Forecast Period2023 to 2032
Base Year2022
Report CoverageGlobal Revenue Forecast, Growth Factors, and Trends, Competitive Landscape, Country wise Analysis and SWOT Analysis
Segments CoveredBy Technology, By End-User, By IBD Type, and By Application
Regions Covered        North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa


Market Dynamics

Driver

Technological advancements

The advancement of technology and the use of AI in cancer diagnostics drive the expansion of the healthcare industry. The artificial tools require low-cost diagnostic processes and quick detection data reporting, this element is observed to promote the adoption of AI-systems in the healthcare infrastructure. Furthermore, government spending on healthcare technology drives the expansion of the healthcare fields in emerging nations.

Restraint

Ethical concerns

One downside of AI in healthcare is the possibility of ethical and privacy issues. In healthcare, AI systems rely extensively on patient data, particularly sensitive medical information. It is critical that this data is collected, stored, and used in a secure and privacy-conscious manner. Patient privacy, data confidentiality, and limiting unauthorized access to personal health information are all important factors.

Opportunity

Integration of image identification

AI image identification methods for endoscopy, pathology, and cross-sectional imaging will be applied in IBD applications in the near future. AI can analyze medical imaging data, such as endoscopy or MRI scans, to detect subtle changes in the intestines that may indicate the onset or progression of IBD. Early detection can lead to more timely and effective treatments. AI can continuously monitor and track the progression of IBD in patients, providing real-time data to healthcare providers and altering them to any significant changes.

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Market Key Players:

  • IBM
  • Google AI
  • Microsoft
  • GE Healthcare
  • Johnson & Johnson
  • Philips Healthcare
  • Nuance Communications
  • Zebra Technologies
  • Medtronic
  • Boston Scientific
  • Olympus

Market Segmentation:

By Technology

  • Machine Learning
  • Natural Language Processing
  • Context-Aware Computing
  • Computer Vision

By End-User

  • Consumer Healthcare
  • Pharmaceutical Companies
  • Research And Development Sector

By IBD Type

  • Crohn’s Disease
  • Ulcerative Colitis

By Application

  • Diagnosis
  • Prognosis
  • Treatment
  • Monitoring 

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

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