According to FutureWise analysis the market for Artificial Intelligence in Digital Pathology in 2023 is US$ 0.33 billion, and is expected to reach US$ 1.17 billion by 2031 at a CAGR of 17%.
Digital pathology refers to the digitization of pathology processes, encompassing the acquisition, management, sharing, and interpretation of pathological information derived from digitized specimen slides. This field employs Whole Slide Imaging (WSI), also known as virtual microscopy, which transforms traditional microscopic slides into digital images for easier analysis, management, and sharing via Whole Slide Scanners. A Whole Slide Scanner is a high-end microscope specifically designed to capture these images using a built-in camera. The digitization of slides enhances the analysis process, reduces errors, provides better and magnified views, facilitates network sharing of slides, and supports remote primary diagnostic work, teleconsultation, and virtual education.
Artificial Intelligence (AI) refers to the intelligence demonstrated by machines that perform actions within specific environments to achieve particular goals. This groundbreaking technology is increasingly being applied in various fields, including digital pathology. The integration of AI with digital pathology has the potential to revolutionize image-based diagnostics. Intelligent algorithms can be developed to identify both general and specific patterns, enabling reliable predictions about patient diseases, including potential outcomes. This offers new levels of hope and care within the field of pathology.
The synergy between AI and digital pathology also leads to increased efficiency, shorter turnaround times, and a reduction in manual errors. AI-driven tools in digital pathology represent a significant advancement compared to traditional molecular and genomic tests, which are currently considered the primary "high-value" tests capable of predicting recurrence and treatment response. Traditional diagnostic methods often involve lengthy processing times and are susceptible to errors. In contrast, AI-based pathology utilizes automated diagnostic tools, delivering results more quickly and minimizing error risks through software quality control, while promoting a more holistic and collaborative approach to patient care.
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Artificial Intelligence in Digital Pathology Market Segmentation:
By Neural Network Type
By Product
By Type
By Application
By End User
By Region
Competitive Landscape in the Artificial Intelligence in Digital Pathology Market:
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**Objectives of this Study: **