AI-Driven Digital Pathology Market Expanding Fast - D845.4 Million by 2030 | Valuates Reports

PR Newswire · 10/17 15:37

BANGALORE, India, Oct. 17, 2024 /PRNewswire/ -- AI in Digital Pathology Market is Segmented by Type (Diagnosis Support, Predictive Modeling, Pattern Recognition, Image Analysis and Detection), by Application (Hospital, Diagnostic Centers, Laboratories & Research Institutes): Global Opportunity Analysis and Industry Forecast, 2024-2030.

The Global AI in Digital Pathology Market was valued at USD 235 Million in 2023 and is anticipated to reach USD 845.4 Million by 2030, witnessing a CAGR of 18.2% during the forecast period 2024-2030.

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Major Factors Driving the Growth of AI in Digital Pathology Market:

The AI in Pathology Market is expected to experience significant growth in the coming years due to increasing investments in AI technologies, a global shortage of pathologists, and the rising demand for more accurate and efficient diagnostic tools. The market is driven by advancements in AI-powered image analysis, diagnostic support tools, and the growing adoption of digital pathology. As healthcare systems worldwide aim to improve diagnostic capabilities, the AI in Pathology Market is set for robust expansion.

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TRENDS INFLUENCING THE GROWTH OF THE AI IN DIGITAL PATHOLOGY MARKET:

Image analysis and detection technologies are at the forefront of driving the AI in Pathology Market. The ability of AI to accurately process and analyze digital pathology images at a much faster rate than human pathologists improves diagnostic accuracy and efficiency. This capability enables healthcare providers to detect abnormalities earlier, particularly in oncology and complex diseases, where precise image analysis is critical. As AI-driven image analysis becomes more advanced, healthcare systems increasingly adopt these tools, which propels the growth of the AI in Pathology Market.

The growing reliance on AI for diagnostic support is a significant factor driving the AI in Pathology Market. AI tools assist pathologists in interpreting complex cases by providing automated insights and reducing the margin of error. This enhanced support improves decision-making and leads to faster, more accurate diagnoses. As hospitals and clinics strive to improve patient outcomes, the integration of AI-powered diagnostic support systems is becoming essential, thus fueling the demand for AI applications in pathology.

Hospitals are key contributors to the growth of the AI in Pathology Market due to their increasing adoption of AI-based solutions to enhance operational efficiency and diagnostic accuracy. AI tools help hospitals streamline workflows, reduce human errors, and improve patient management. By integrating AI in pathology, hospitals can significantly shorten diagnosis times, thereby improving treatment decisions and patient care. This growing demand for AI integration in hospitals is expected to drive the expansion of the AI in Pathology Market.

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The complexity of modern pathological cases, especially in areas like cancer diagnosis, has created a need for more advanced diagnostic tools, driving the adoption of AI in pathology. AI's ability to process vast amounts of data quickly and identify subtle patterns in pathology slides supports pathologists in making more informed decisions. This complexity requires precision, which AI solutions offer, leading to greater demand for AI in pathology.

A global shortage of trained pathologists has led to the increased adoption of AI tools to fill the gap in diagnostic capabilities. AI can enhance the productivity of existing pathologists by automating routine tasks, allowing them to focus on more critical cases. This helps alleviate the burden on healthcare systems facing personnel shortages, making AI a valuable tool in maintaining diagnostic efficiency. Consequently, the demand for AI in pathology continues to grow.

 Healthcare providers are under increasing pressure to improve diagnostic accuracy, particularly in high-stakes fields like oncology. AI tools, with their ability to reduce human error and improve the consistency of diagnoses, are becoming essential in pathology departments. By offering high precision and the ability to learn from vast datasets, AI technologies are helping pathologists provide more accurate and consistent results, which is driving market growth.

The growing trend of personalized medicine has increased the demand for precise and rapid diagnostics, driving the adoption of AI in pathology. AI's capacity to analyze individual patient data and offer tailored diagnostic insights supports the development of personalized treatment plans. This shift towards individualized care, especially in cancer and genetic disorders, necessitates advanced pathology solutions, thereby pushing the demand for AI-driven tools in the pathology market.

The shift from traditional pathology methods to digital pathology is creating opportunities for AI to integrate into clinical workflows. Digital pathology enables the use of AI tools to process and analyze pathology slides more efficiently. This transformation is being driven by the need for more streamlined and accurate diagnostics, further fueling the adoption of AI solutions within pathology departments across hospitals and research institutions.

DIGITAL PATHOLOGY MARKET SHARE:

The AI in Pathology Market shows varying levels of growth across different regions, with North America leading due to its advanced healthcare infrastructure and early adoption of AI technologies. Europe is following closely, driven by significant investments in healthcare innovation. In the Asia-Pacific region, rapid advancements in healthcare, increasing investments, and rising awareness of AI technologies are contributing to the growing market. Latin America and Africa are expected to experience gradual adoption as healthcare infrastructure and technological integration progress.

Key Companies:

  • PathAI
  • Proscia, Inc.
  • Aiforia
  • Deep Bio
  • LBP
  • CellaVision AB
  • AIRA Matrix
  • Indica Labs
  • DoMore Diagnostics
  • Mindpeak
  • Dipath
  • iDeepwise
  • Syntropy
  • Evidium

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