The artificial intelligence in pathology market size has grown rapidly in recent years, moving from $1.08 billion in 2023 to $1.22 billion in 2024 at a CAGR of 13.5%. This growth in the historical period can be attributed to factors such as an increased prevalence of diseases, higher funding initiatives, expanding use of telemedicine, supportive government initiatives, and rising demand for pathology services. The AI in pathology market is projected to grow to $2.04 billion by 2028 at a CAGR of 13.6%. This anticipated growth can be linked to the increased role of AI in clinical trials, expanding healthcare infrastructure, interdisciplinary collaborations, the development of ethical guidelines, and advancements in AI-based predictive analytics. Key trends forecasted for this period include development of AI-powered diagnostic tools, integration with electronic health records (EHRs), computer-aided diagnosis (CAD), AI-driven biomarker discovery, and integration of AI with genomic data.
Global Artificial Intelligence In Pathology Market Key Driver
The increasing need for personalized medicine is projected to propel the growth of AI in pathology. Personalized medicine focuses on customizing healthcare treatments based on individual characteristics and needs. AI aids this by enabling more accurate analysis of medical data, improving diagnosis, and developing tailored treatment plans. According to the Personalized Medicine Coalition, 12 new personalized medicines were approved in 2022, accounting for about 34% of all new therapies, reflecting significant growth compared to previous years. Therefore, the demand for personalized medicine drives the AI in pathology market.
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Global Artificial Intelligence In Pathology Market Segments
The artificial intelligence in pathology market 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
By Geography:The regions covered in the artificial intelligence in pathology market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Asia-Pacific was the largest region in the artificial intelligence in pathology market in 2023. North America is expected to be the fastest-growing region in the forecast period.
Major Artificial Intelligence In Pathology Industry Players
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.
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Artificial Intelligence In Pathology Market Overview
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.
Artificial Intelligence In Pathology Global Market Report 2023 provides data on the global artificial intelligence in pathology market such as market size, growth forecasts, segments and geographies, competitive landscape including leading competitors’ revenues, profiles and market shares. The artificial intelligence in pathology market report identifies opportunities and strategies based on market trends and leading competitors’ approaches.
