What is the current market size and future outlook for the artificial intelligence in pathology market?
The artificial intelligence in pathology market size has grown rapidly in recent years. It will grow from $1.22 billion in 2024 to $1.39 billion in 2025 at a compound annual growth rate (CAGR) of 13.8%. The growth in the historic period can be attributed to increasing prevalence of disease, increasing funding initiatives, increasing use of telemedicine, increasing government initiatives, and increasing the demand for pathology services.
The artificial intelligence in pathology market size is expected to see rapid growth in the next few years. It will grow to $2.31 billion in 2029 at a compound annual growth rate (CAGR) of 13.5%. The growth in the forecast period can be attributed to the growth of AI in clinical trials, expanding healthcare infrastructure, interdisciplinary collaborations, the development of clear ethical guidelines, and the development of AI-based predictive analytics. Major trends in the forecast period include development of AI-powered diagnostic tools, integration with electronic health records, computer-aided diagnosis (CAD), AI-driven biomarker discovery, and integration with genomic data.
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How has the artificial intelligence in pathology market evolved, and what factors have shaped its growth?
The increasing need for personalized medicine is expected to propel the growth of artificial intelligence in pathology market going forward. Personalized medicine refers to tailoring medical treatment and healthcare to the individual characteristics, needs, and preferences of each patient. The increasing need for personalized medicine is due to tailor treatments to individual genetic profiles, lifestyle factors, and specific disease characteristics, thereby improving efficacy and reducing adverse effects. Artificial intelligence (AI) in pathology helps personalized medicine by enabling more accurate and efficient analysis of medical images and genetic data, thus allowing for more precise diagnosis, better identification of disease subtypes, and tailored treatment plans that align with an individual’s unique biological profile. For instance, in February 2023, according to a report published by the Personalized Medicine Coalition, a US-based professional membership organization, the approval of 12 new personalized medicines in 2022, accounting for around 34% of all new therapies, reflected a significant rise compared to previous years. Therefore, the increasing need for personalized medicine is driving the growth of artificial intelligence in pathology market.
What are the major segments of the artificial intelligence in pathology market?
The artificial intelligence in pathologymarket covered in this report is segmented –
1) By Component: Software, Scanners
2) By Neural Network: Generative Adversarial Networks, Convolutional Neural Networks, Conventional Neural Network, Recurrent Neural Networks, Other Neural Networks
3) By Application: Drug Discovery, Disease Diagnosis And Prognosis, Clinical Workflow, Training And Education
4) By End User: Pharmaceutical And Biotechnology Companies, Hospitals And Reference Laboratories, Academic And Research Institutes
Subsegments:
1) By Software: Image Analysis Software, Diagnostic Workflow Software, Predictive Analytics Software
2) By Scanners: Whole Slide Imaging Scanners, Digital Pathology Scanners, Multi-Spectral Imaging Scanners
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Which companies dominate the artificial intelligence in pathology market?
Major companies operating in the artificial intelligence in pathology market are F. Hoffmann-La Roche Ltd., Koninklijke Philips N.V., Hamamatsu Photonics K.K., Leica Biosystems, Tempus Labs Inc., Spectra AB, Lunit Inc., Paige AI Inc., Inspirata Inc., Indica Labs Inc., Flagship Biosciences Inc., Proscia Inc., Aiforia Technologies Oy, Lumea Inc., Optrascan Inc., PathAI Inc., Visiopharm A/S, Ibex Medical Analytics Ltd., BioSymetrics Inc., Deep Bio Inc., Konfoong Biotech International Co Ltd., Mindpeak GmbH, Qritive Inc., Vuno Inc.
How will evolving trends contribute to the growth of the artificial intelligence in pathology market?
Major companies operating in the artificial intelligence in pathology market are focusing on developing advanced solutions, such as advanced cancer detection tools, to enhance diagnostic accuracy, streamline workflows, and improve patient outcomes. Advanced cancer detection tools using AI leverage machine learning algorithms and deep learning models to analyze medical images and pathology slides, enhancing the accuracy of tumor detection and classification. For instance, in March 2022, Paige.ai, a US-based digital pathology company, launched Paige Lymph Node Module to assist pathologists in detecting breast cancer metastases in lymph nodes. It offers unique features such as over 98% sensitivity in detecting breast cancer metastases of any size, including small micrometastases, and utilizes a proprietary TissueMap to highlight suspicious areas on lymph node slides, enhancing the efficiency and accuracy of pathologists’ reviews while significantly reducing the time required for analysis.
What are the key regional dynamics of the artificial intelligence in pathology market, and which region leads in market share?
Asia-Pacific was the largest region in the artificial intelligence in pathology market in 2024. North America is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence in pathology market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Artificial Intelligence In Pathology Market Report 2025 Offer?
The artificial intelligence in pathology market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Artificial intelligence (AI) in pathology involves the use of machine learning algorithms and deep learning models to assist in analyzing medical images, identifying patterns, and diagnosing diseases. AI helps pathologists automate tasks such as slide analysis, tumor detection, and grading, improving diagnostic accuracy and efficiency. It also enables faster processing of large datasets, facilitating personalized medicine.
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