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AI in Endoscopy Market - Global Industry, Analysis, Size, Share, Growth, Trends, and Forecasts 2024-2032

Global AI in Endoscopy Market Overview

In the healthcare industry, deep learning (DL), machine learning (ML), and artificial intelligence (Al) are the most prominent trends, especially in the endoscopy field. AI has the potential to improve the quality of endoscopy at all levels.

AI in endoscopy helps in better diagnosis; screening and enhanced detection. Advanced technologies such as AI in endoscopy are safer and more consistent and minimize the workload of surgeons.

Al is mostly used in two areas of endoscopy: computer-aided detection (CADe) and computer-aided diagnosis (CADX). Al has been able to” create an ML model that can determine the risk in patients experiencing upper gastrointestinal (GI) bleeding, confirm the presence of a specific GI condition, and specify the best course of therapy because of technological advancements.

Global AI in Endoscopy Market-Competitive Insights

On September 27, 2022, Iterative Scopes, a pioneer in precision medicine solutions for gastroenterology, announced that the FDA has authorized SKOUT for adult patients undergoing colorectal cancer monitoring via the 510(k) process. Utilizing state-of-the-art computer vision technology, SKOUT is a real-time computer-assisted polyp identification tool that identifies problematic tissue and provides endoscopists with prompt feedback.

On November 11, 2019, AI Medical Service, Inc. produced real-time endoscopic Al software, which is approved by the FDA, and analyzes endoscopy images to potentially diagnose stomach cancer.

Some of the Global AI in Endoscopy Market Include –

  • Medtronic
  • Wision A.I.
  • Olympus Corporation
  • Fujifilm Corporation
  • Pentax Corporation
  • NEC Corporation
  • Odin Vision
  • Magentiq Eye Ltd.
  • Wuhan EndoAngel Medical Technology Company

Global AI in Endoscopy Market – Growth Drivers

The market for AI in endoscopy is expanding significantly, and forecasts for the upcoming years point to a further increase. Major forces behind this expansion include:

Precision in Lesion identification: Artificial intelligence (AI) algorithms improve lesion identification accuracy during endoscopic exams, which is especially important for the early diagnosis of gastrointestinal malignancies.AI systems provide real-time decision assistance during endoscopic operations, assisting medical practitioners in spotting anomalies and coming to well-informed conclusions.

AI systems are quite effective in characterizing polyps and can differentiate between benign and possibly malignant tumors, which allows for more accurate treatment planning. In Endoscopic Imaging the use of AI in conjunction with endoscopic imaging technology improves treatment planning and diagnostic performance. Advances in Endoscopic Imaging include training and education for healthcare professionals, Combining AI with endoscopic imaging technology improves diagnostic capabilities and treatment plans. To properly use AI in endoscopy, healthcare personnel must get thorough training and instruction.

As technology advancements continue to transform the diagnosis and treatment of gastrointestinal disorders, the industry is poised for exponential growth. Artificial intelligence is becoming an essential tool for endoscopic treatments.                    

Global AI in Endoscopy Market-Restraints

The Al in Endoscopy market has certain obstacles despite its encouraging growth prospects:

Lack of Standardization and Regulatory Frameworks: The absence of established standards and regulatory frameworks in the emerging field of Al in endoscopic is impeding the broad use of Al-enabled endoscopic solutions.

Concerns about Data Privacy and Security: Since endoscopy depends so much on patient data, especially private medical information, it is essential to secure patient confidentiality and adhere to data protection laws.

High Implementation Costs: A substantial investment in training, infrastructure, and resources is needed for the deployment of Al-powered endoscopic devices and software. These technologies’ high costs could prevent them from being widely used, especially in healthcare settings with limited resources.

Global AI in Endoscopy Market-Opportunities

Advancements in Al algorithms and techniques, such as reinforcement learning and unsupervised learning, enhance efficiency and diagnostic capabilities in Al-powered systems. Integration with other diagnostic technologies like AR and VR can improve visualization and interpretation of endoscopic images.

Emerging markets offer growth opportunities for Al in Endoscopy due to increasing healthcare expenditure, infrastructure improvement, and diagnostic technology awareness. Strategic partnerships between Al technology providers, manufacturers, and healthcare institutions can accelerate the development and commercialization of Al-enabled endoscopy solutions.

Global AI in Endoscopy Market-Geographical Insights

The AI in Endoscopy market is experiencing significant growth in regions such as North America, Europe, and Asia Pacific. This growth is driven by factors such as robust healthcare infrastructure, high healthcare expenditure, well-established healthcare systems, and a growing burden of gastrointestinal diseases. The Latin American market is also witnessing growth due to improved healthcare infrastructure, increased expenditure, and demand for minimally invasive procedures. The Middle East and Africa are also adopting AI in Endoscopy. The market is expected to grow at a CAGR of 37.8% and reach US$ 738.9 million by 2031.

  Global AI in the endoscopy market – a key development

  • On October 5, 2022, Virgo, Satisfai Health, and Alimentiv announced an official partnership to use Al-assisted technology to improve clinical trials in inflammatory bowel disease (IBD) and other Gl disorders.
  • On November 13, 2021, Wision A.I. Ltd, a startup company in the field of Al-assisted healthcare diagnostics, announced the expansion of its product portfolio with 510(k) clearance of the U.S. FDA for EndoScreener. It is a real-time diagnosis software that helps endoscopists provide a sound alarm and visual notification for polyp detection during colonoscopy.
  • On 23, October 2020, Olympus Corporation, a leading manufacturer of optical and digital precision technology, announced a collaboration with Cybernet Systems Co., Ltd. To provide CAE (Computer Aided Engineering) software for computation/visualization. This agreement is expected to help Olym establish an Al diagnostic support system at the Asian Institute of Gastroenterology (AIG), India.
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Research Methodology: Aspects

Market research is a crucial tool for organizations aiming to navigate the dynamic landscape of customer preferences, business trends, and competitive landscapes. At Cognizance Market Research, acknowledging the importance of robust research methodologies is vital to delivering actionable insights to our clientele. The significance of such methodologies lies in their capability to offer clarity in complexity, guiding strategic management with realistic evidence rather than speculation. Our clientele seek insights that excel superficial observations, reaching deep into the details of consumer behaviours, market dynamics, and evolving opportunities. These insights serve as the basis upon which businesses craft tailored approaches, optimize product offerings, and gain a competitive edge in an ever-growing marketplace.

The frequency of information updates is a cornerstone of our commitment to providing timely, relevant, and accurate insights. Cognizance Market Research adheres to a rigorous schedule of data collection, analysis, and distribution to ensure that our reports reflect the most current market realities. This proactive approach enables our clients to stay ahead of the curve, capitalize on emerging trends, and mitigate risks associated with outdated information.

Our research process is characterized by meticulous attention to detail and methodological rigor. It begins with a comprehensive understanding of client objectives, industry dynamics, and research scope. Leveraging a combination of primary and secondary research methodologies, we gather data from diverse sources including surveys, interviews, industry reports, and proprietary databases. Rigorous data analysis techniques are then employed to derive meaningful insights, identify patterns, and uncover actionable recommendations. Throughout the process, we remain vigilant in upholding the highest standards of data integrity, ensuring that our findings are robust, reliable, and actionable.

Key phases involved in in our research process are mentioned below:


Understanding Clients’ Objectives:

Extensive Discussions and Consultations:

  • We initiate in-depth discussions and consultations with our clients to gain a comprehensive understanding of their objectives. This involves actively listening to their needs, concerns, and aspirations regarding the research project.
  • Through these interactions, we aim to uncover the underlying motivations driving their research requirements and the specific outcomes they hope to achieve.

Industry and Market Segment Analysis:

  • We invest time and effort in comprehensively understanding our clients’ industry and market segment. This involves conducting thorough research into market trends, competitive dynamics, regulatory frameworks, and emerging opportunities or threats.
  • By acquiring a deep understanding of the broader industry landscape, we can provide context-rich insights that resonate with our clients’ strategic objectives.

Target Audience Understanding:

  • We analyze our clients’ target audience demographics, behaviors, preferences, and needs to align our research efforts with their consumer-centric objectives. This entails segmenting the audience based on various criteria such as age, gender, income level, geographic location, and psychographic factors.
  • By understanding the nuances of the target audience, we can tailor our research methodologies to gather relevant data that illuminates consumer perceptions, attitudes, and purchase intent.


Identifying Challenges and Opportunities:

  • We proactively identify the challenges and opportunities facing our clients within their respective industries. This involves conducting SWOT (Strengths, Weaknesses, Opportunities, Threats) analyses and competitive benchmarking exercises.
  • By identifying potential obstacles and growth drivers, we can provide strategic recommendations that help our clients navigate complexities and capitalize on emerging opportunities effectively.

Grasping Specific Goals:

  • We delve into the intricacies of our clients’ objectives to gain clarity on the specific goals they aim to accomplish through the research. This entails understanding their desired outcomes, such as market expansion, product development, or competitive analysis.
  • By gaining a nuanced understanding of our clients’ goals, we can tailor our research approach to address their unique challenges and opportunities effectively.

Data Collection:


Primary Research Process:

  • Surveys: We design and administer surveys tailored to capture specific information relevant to our clients’ objectives. This may involve employing various survey methodologies, such as online, telephone, or face-to-face interviews, to reach target audiences effectively.
  • Interviews: We conduct structured or semi-structured interviews with key stakeholders, industry experts, or target consumers to gather in-depth insights and perspectives on relevant topics. These interviews allow us to probe deeper into specific issues and uncover valuable qualitative data.
  • Focus Groups: We organize focus group discussions with carefully selected participants to facilitate interactive discussions and gather collective opinions, attitudes, and preferences. This qualitative research method provides rich contextual insights into consumer behaviors and perceptions.
  • Observations: We conduct observational research by directly observing consumer behaviors, interactions, and experiences in real-world settings. This method enables us to gather objective data on consumer actions and reactions without relying on self-reported information.

Secondary Research Process:

  • Literature Review: We conduct comprehensive literature reviews to identify existing studies, academic articles, and industry reports relevant to the research topic. This helps us gain insights into previous research findings, theoretical frameworks, and best practices.
  • Industry Reports: We analyze industry reports published by reputable trade associations (whitepapers, research studies, etc.), and government agencies (U.S. Census Bureau, Bureau of Labor Statistics, and Securities and Exchange Commission etc.) to obtain macro-level insights into market trends, competitive landscapes, and industry dynamics.
  • Government Publications: We review government publications, such as economic reports, regulatory documents, and statistical databases, to gather relevant data on demographics, market size, consumer spending patterns, and regulatory frameworks.
  • Online Databases: We leverage online databases, such as industry portals, and academic repositories (PubMed Central (PMC), ScienceDirect, SSRN (Social Science Research Network), Directory of Open Access Journals (DOAJ), NCBI, etc.), to access a wide range of secondary data sources, including market statistics, financial data, and industry analyses.



Data Analysis:

The data analysis phase serves as a critical juncture where raw data is transformed into actionable insights that inform strategic decision-making. Through the utilization of analytical methods such as statistical analysis and qualitative techniques like thematic coding, we uncover patterns, correlations, and trends within the data. By ensuring the integrity and validity of our findings, we strive to provide clients with accurate and reliable insights that accurately reflect the realities of the market landscape.


Transformation of Raw Data:

  • Upon collecting the necessary data, we transition into the data analysis phase, where raw data is processed and transformed into actionable insights. This involves organizing, cleaning, and structuring the data to prepare it for analysis.

Utilization of Analytical Methods:

  • Depending on the research objectives, we employ a diverse range of analytical methods to extract meaningful insights from the data. These methods include statistical analysis, trend analysis, regression analysis, and qualitative coding.

Statistical Analysis:

  • Statistical tools are instrumental in uncovering patterns, correlations, and trends within the data. By applying statistical techniques such as descriptive statistics, hypothesis testing, and multivariate analysis, we can discern relationships and derive valuable insights.

Qualitative Analysis Techniques:

  • In addition to quantitative analysis, we leverage qualitative analysis techniques to gain deeper insights from qualitative data sources such as interviews or open-ended survey responses. One such technique is thematic coding, which involves systematically categorizing and interpreting themes or patterns within qualitative data.

Integrity and Validity Maintenance:

  • Throughout the analysis process, we maintain a steadfast commitment to upholding the integrity and validity of our findings. This entails rigorous adherence to established methodologies, transparency in data handling, and thorough validation of analytical outcomes.

Data Validation:

The final phase of our research methodology is data validation, which is essential for ensuring the reliability and credibility of our findings. Validation involves scrutinizing the collected data to identify any inconsistencies, errors, or biases that may have crept in during the research process. We employ various validation techniques, including cross-referencing data from multiple sources, conducting validity checks on survey instruments, and seeking feedback from independent experts or peer reviewers. Additionally, we leverage internal quality assurance protocols to verify the accuracy and integrity of our analysis. By subjecting our findings to rigorous validation procedures, we instill confidence in our clients that the insights they receive are robust, reliable, and trustworthy.


Importance of Data Validation:

  • Data validation is the final phase of the research methodology, crucial for ensuring the reliability and credibility of the findings. It involves a systematic process of reviewing and verifying the collected data to detect any inconsistencies, errors, or biases.

Scrutiny of Collected Data:

  • The validation process begins with a thorough scrutiny of the collected data to identify any discrepancies or anomalies. This entails comparing data points, checking for outliers, and verifying the accuracy of data entries against the original sources.

Validation Techniques:

  • Various validation techniques are employed to ensure the accuracy and integrity of the data. These include cross-referencing data from multiple sources to corroborate findings, conducting validity checks on survey instruments to assess the reliability of responses, and seeking feedback from independent experts or peer reviewers to validate the interpretation of results.

Internal Quality Assurance Protocols:

  • In addition to external validation measures, internal quality assurance protocols are implemented to further validate the accuracy of the analysis. This may involve conducting internal audits, peer reviews, or data validation checks to ensure that the research process adheres to established standards and guidelines.
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