세계의 병리학용 AI 시장 - 시장 규모, 점유율, 동향 분석 보고서 : 뉴럴 네트워크별, 용도별, 최종 사용자별, 컴퍼넌트별, 지역별 전망 및 예측(2023-2030년)

The Global AI in Pathology Market size is expected to reach $66.3 million by 2030, rising at a market growth of 15.8% CAGR during the forecast period.

Collaborations enable the seamless integration of these technologies into pathology workflows for enhanced diagnostics. Healthcare companies provide valuable clinical data and pathology images, while tech companies offer data management, analytics, and artificial intelligence expertise. Consequently, the disease diagnosis & prognosis segment would generate approximately 25.12% share of the market by 2030. Leveraging advanced machine learning algorithms, AI systems analyze vast amounts of pathological data with unprecedented speed and accuracy, aiding pathologists in identifying and classifying diseases. Some of the factors affecting the market are growing digitalization of pathology, increasing demand for personalized medicine, and high cost of digital pathology systems.

Digital pathology provides high-resolution digital images that can be analyzed more efficiently than traditional microscopy. AI algorithms leverage these images to identify patterns, anomalies, and specific features relevant to disease diagnosis. The digitalization of pathology generates large datasets. AI excels in analyzing big data, extracting patterns, and identifying correlations that may not be easily discernible through traditional methods. Thus, the growing digitalization of pathology will expand the market growth in the coming years. Moreover, AI algorithms analyze pathological data to identify and validate biomarkers associated with specific diseases. These biomarkers serve as indicators for personalized treatment strategies, allowing for more targeted and effective interventions. Thus, the increasing need for personalized medicine is a driving force behind the expansion of market.

The upfront cost of acquiring and implementing digital pathology systems, including whole-slide imaging scanners, software platforms, and associated infrastructure, can be substantial. This initial investment may pose financial challenges for healthcare institutions, particularly smaller laboratories or those with limited budgets. Training pathologists and laboratory staff to effectively use digital pathology systems and AI tools adds to the overall cost. Due to the above factors, market growth will be hampered in the coming years.

Neural Network Outlook

Based on neural network, the market is fragmented into generative adversarial networks (GANs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and others. The generative adversarial networks (GANs) segment garnered a significant revenue share in the market in 2022. GANs are widely utilized for generating realistic images. They have been applied in creating high-resolution images, art generation, and deepfake generation. GANs are employed for data augmentation in various domains, generating additional training samples to enhance model robustness. They can enhance the resolution of images, generating high-quality versions of low-resolution input images. GANs can generate realistic images from textual descriptions, bridging the gap between natural language and graphic content.

Application Outlook

By application, the market is categorized into drug discovery, disease diagnosis & prognosis, clinical workflow, and others. In 2022, drug discovery registered the highest revenue share in the market. AI algorithms can analyze large-scale datasets resulting from high-throughput screening processes. This includes the analysis of cell cultures, histopathological images, and other data generated in drug discovery pipelines. The automation of analysis tasks expedites the identification of potential drug candidates. AI can examine the interactions between drugs and biological pathways. Understanding how drugs affect specific pathways in the context of disease pathology helps rationalize interventions and identify potential synergies or antagonisms.

End User Outlook

On the basis of end user, the market is classified into pharmaceutical & biotechnology companies, hospitals & reference laboratories, and academic & research institutes. The hospitals & reference laboratories segment covered a considerable revenue share in the market in 2022. AI supports the implementation of digital pathology, where glass slides are digitized for remote viewing and analysis. This facilitates collaboration, second opinions, and consultations among pathologists within the hospital or across different locations. AI is a decision support system for pathologists, providing real-time assistance during the diagnostic process. AI can be used for continuous learning and training programs for pathologists. Virtual simulations, interactive learning modules, and AI-assisted training contribute to ongoing professional development.

Component Outlook

On the basis of component, the market is segmented into software and scanners. The software segment acquired a substantial revenue share in the market in 2022. This significant share can be attributed to pathologists' widespread acceptance and utilization of AI-based software. High adaptability, interoperability, and the automation of a variety of pathology responsibilities, including image analysis, data extraction, and report generation, are a few of the benefits of the software segment. The adoption and development of AI software in pathology are propelled by these factors, which offer significant prospects for progress in disease detection, diagnosis, and treatment planning.

Regional Outlook

Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. The Asia Pacific region acquired a substantial revenue share in the market in 2022. The region's large and diverse patient population provides a wealth of data for training and validating AI algorithms. AI models in pathology benefit from the diversity of patient demographics and disease presentations, enhancing their generalizability. Collaboration between healthcare providers and technology companies, including those specializing in AI, accelerates developing and deploying AI solutions in pathology across the Asia Pacific region.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Koninklijke Philips N.V., F. Hoffmann-La Roche Ltd., Hologic, Inc., Visiopharm A/S, Paige AI, Inc., PathAI, Inc., Aiforia Technologies Plc, Indica Labs, Inc., Optrascan, Inc. (Optra Ventures, LLC), MindPeak GmbH.

Recent Strategies Deployed in AI in Pathology Market

Partnerships, Collaborations & Agreements:

Oct-2023: F. Hoffmann-La Roche Ltd. has entered into a collaboration with Ibex Medical Analytics Ltd. to provide AI-powered solutions for cancer detection, along with the support of Amazon Web Services, Inc., a cloud service provider. This collaboration aims to give pathology laboratories access to Ibex's AI-driven decision support tools through the navify Digital Pathology software platform. Through this integration, clinicians can receive assistance in the diagnosis of breast and prostate cancer.

Sep-2023: Hologic, Inc. has partnered with Bayer AG to introduce contrast-enhanced mammography (CEM) solutions for improved breast cancer detection in European, Canadian, and Asia Pacific regions. The partnership aims to combine Bayer and Hologic's technologies to facilitate contrast media application in mammography examinations. The partnership focuses on providing radiologists with comprehensive product packages, hands-on training, and seamless integration of CEM into their workflows.

Jul-2023: Aiforia Technologies Plc and Orion Corporation, a Finnish pharmaceutical company, have entered into a collaboration to jointly create artificial intelligence (AI)-driven image analysis solutions for preclinical research and product development. Through this collaboration, Aiforia gains valuable insights from Orion regarding the specific needs of its preclinical customer base. This collaboration empowers Aiforia to refine and customize its product portfolio, ensuring a more targeted approach to meet the unique requirements of the preclinical research community.

Jun-2023: Visiopharm A/S has entered into a collaboration with Minerva Imaging, a preclinical Contract Research Organization (CRO) that specializes in molecular imaging services. Within this collaboration, the two companies will focus on developing AI-based image analysis applications in histology. The collaboration between Minerva and Visiopharm aims to expedite the creation of a toolbox for AI-driven precision pathology. This advancement will empower pharmaceutical companies to enhance clinical development by improving both quantitative and qualitative assessments, particularly in challenging-to-treat cancers.

Jun-2023: Visiopharm A/S has formed a partnership with Grundium Ltd., a well-known provider of high-quality imaging solutions for digital pathology. Through this partnership, the companies aim to broaden the accessibility of digital pathology solutions for clinics and laboratories globally. Within this partnership, Visiopharm will make Grundium's Ocus scanners available alongside its Qualitopix solution. This integration allows labs to automatically upload images for processing. The Qualitopix solution provides labs with the capability to improve staining quality and standardization by monitoring staining consistency.

Jun-2023: MindPeak GmbH has established a partnership with Proscia Inc., a U.S.-based provider of digital and computational pathology solutions. This partnership aims to provide closely integrated AI-powered workflows, supporting pathologists in making more efficient, informed, and reproducible clinical decisions. The goal is to broaden access to improved diagnoses for cancer patients.

Apr-2023: Optrascan, Inc. has formed a collaboration with Lumea Inc., a global leader in integrated digital pathology solutions. This collaboration combines Lumia's comprehensive digital pathology platform with diverse digital scanning solutions, aiming to facilitate the efficient and cost-effective adoption of digital pathology by providers.

Apr-2023: Indica Labs, Inc. and Lunit Inc., a medical software company, have entered into an agreement. As part of this agreement, the two companies will offer a completely interoperable solution, connecting Indica Labs' HALO AP image management software platform with Lunit's suite of AI pathology products. The Collaboration facilitates the smooth integration of Lunit's AI pathology solutions, including Lunit SCOPE PD-L1 designed for non-small cell lung cancer, into the HALO AP platform. It's worth noting that HALO AP holds CE-IVD certification as a clinical image management platform.

Apr-2023: PathAI, Inc. has partnered with ConcertAI LLC, a leading provider of AI software-as-a-service (SaaS) for life sciences and healthcare. The partnership aims to introduce an innovative solution that combines PathAI's PathExplore tumor microenvironment panel with ConcertAI's Patient360 and RWD360 products. This partnership will result in a groundbreaking quantitative histopathology and curated clinical real-world data (RWD) solution. The goal is to offer researchers access to a unique quantitative pathology dataset, allowing exploration beyond the limitations of small, controlled datasets. This includes identifying and analyzing novel histological biomarkers correlated with patient treatment and outcomes.

Mar-2023: Paige AI, Inc. has expanded its Partnership with Leica Biosystems Nussloch GmbH, a leading cancer diagnostics firm. The primary goal of this enhanced partnership is to further progress the adoption of digital pathology workflows across hospitals and laboratories worldwide. As part of this Partnership, Paige will provide software-as-a-service (SaaS) solutions for managing and viewing digital pathology images. Additionally, Paige will integrate various artificial intelligence (AI) solutions directly into the Aperio GT 450 digital pathology slide scanners within Leica Biosystems' product range.

Feb-2022: MindPeak GmbH and Crosscope Inc. have entered into an partnership, integrating MindPeak's image analysis tools into Crosscope's Digital Pathology platform. This partnership enhances Crosscope's AI capabilities, enabling them to provide comprehensive digital pathology solutions. By seamlessly integrating advanced AI tools, the partnership aims to optimize Histopathology workflows, supporting pathologists in improving lab efficiency and delivering timely and impactful diagnoses for ER, PR, and Ki-67 IHC stainings. The integration promises to positively influence patient treatment outcomes.

Oct-2021: F. Hoffmann-La Roche Ltd. and PathAI, Inc. have entered into an agreement to work on the development and distribution of an integrated image analysis workflow tailored for pathologists. Under this agreement, the objective is to jointly create a seamless workflow that incorporates PathAI's AI-powered image analysis algorithms into NAVIFY Digital Pathology, which is Roche's cloud-based iteration of the uPath enterprise software.

Aug-2020: Hologic, Inc. has entered into a collaboration with RadNet, Inc., a leading provider of high-quality outpatient diagnostic imaging services. The collaboration aims to promote the utilization of artificial intelligence (AI) in breast health. As part of this collaboration, RadNet plans to upgrade all its Hologic mammography systems to incorporate Hologic's 3DQuorum imaging technology, which is powered by Genius AI. This technology, working in conjunction with Clarity HD high-resolution imaging technology, significantly reduces tomosynthesis image volume for radiologists by 66 percent.

Product Launches & Product Expansions:

May-2022: Koninklijke Philips N.V. has introduced its state-of-the-art AI-driven enterprise imaging portfolio for complex clinical and operational tasks. Philips unveiled the MR 5300 imaging system, integrating AI-driven technologies designed to automate challenging clinical and operational tasks. This innovative technology from Philips empowers patients and healthcare professionals to harness the power of data for advanced analytics. This development sets the stage for a streamlined and precise diagnostic platform, enhancing both patient and healthcare provider experiences.

Mar-2022: Paige AI, Inc. has launched Paige Breast Lymph Node, an innovative AI medical software aiding pathologists in detecting the spread of breast cancer to lymph nodes. The product enhances efficiency and accuracy, utilizing AI to identify at-risk metastases, including small micrometastases, aiming for over 98% slide-level sensitivity. This advancement seeks to improve diagnostic accuracy for subtle metastatic foci.

Nov-2021: Hologic, Inc. has launched its newest product, the Genius Digital Diagnostics System, now available in Europe. This system integrates deep learning-based AI with advanced volumetric imaging technology to advance cervical cancer screening. The primary goal is to assist in detecting pre-cancerous lesions and cervical cancer cells in women. Using advanced image analysis, the system thoroughly evaluates each cell in a ThinPrep Pap test image, offering a comprehensive view of clinically relevant objects.

Oct-2021: Koninklijke Philips N.V. has introduced its newest digital pathology platform called IntelliSite, designed to cover the entire enterprise. IntelliSite includes a suite of scalable software tools aimed at enhancing workflows, increasing diagnostic confidence, promoting collaboration, incorporating artificial intelligence (AI), and enhancing the overall efficiency of pathology laboratories. Additionally, Philips emphasizes outstanding image quality and advanced algorithms that assist pathologists in both diagnosis and the development of care pathways.

May-2021: Optrascan, Inc. has launched CytoSiA, an intelligent solution for quick and cost-effective scanning and analysis of liquid-based cytology slides and Pap smears. CytoSiA includes OptraSCAN's digital pathology scanner, storage, and advanced AI algorithms, assisting pathologists in screening and detecting cervical cancer, pre-cancerous lesions, atypical cells, and various cytologic categories. It has been adopted globally by many hospitals and pathology labs, leading to improved patient outcomes, increased efficiency, and enhanced productivity in handling cytology cases.

Scope of the Study

Market Segments covered in the Report:

By Neural Network

• Convolutional neural networks (CNNs)
• Generative adversarial networks (GANs)
• Recurrent neural networks (RNNs)
• Others

By Application

• Drug Discovery
• Disease Diagnosis & Prognosis
• Clinical Workflow
• Others

By End User

• Pharmaceutical & Biotechnology Companies
• Hospitals & Reference Laboratories
• Academic & Research Institutes

By Component

• Scanners
• Software

By Geography

• North America
  • US
  • Canada
  • Mexico
  • Rest of North America
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
• LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Companies Profiled

• Koninklijke Philips N.V.
• F. Hoffmann-La Roche Ltd.
• Hologic, Inc.
• Visiopharm A/S
• Paige AI, Inc.
• PathAI, Inc.
• Aiforia Technologies Plc
• Indica Labs, Inc.
• Optrascan, Inc. (Optra Ventures, LLC)
• MindPeak GmbH

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Table of Contents

Chapter 1. Market Scope & Methodology

• 1.1 Market Definition
• 1.2 Objectives
• 1.3 Market Scope
• 1.4 Segmentation
  • 1.4.1 Global AI in Pathology Market, by Neural Network
  • 1.4.2 Global AI in Pathology Market, by Application
  • 1.4.3 Global AI in Pathology Market, by End User
  • 1.4.4 Global AI in Pathology Market, by Component
  • 1.4.5 Global AI in Pathology Market, by Geography
• 1.5 Methodology for the research

Chapter 2. Market at a Glance

• 2.1 Key Highlights

Chapter 3. Market Overview

• 3.1 Introduction
  • 3.1.1 Overview
    • 3.1.1.1 Market Composition and Scenario
• 3.2 Key Factors Impacting the Market
  • 3.2.1 Market Drivers
  • 3.2.2 Market Restraints

Chapter 4. Competition Analysis - Global

• 4.1 Market Share Analysis, 2022
• 4.2 Recent Strategies Deployed in AI in Pathology Market
• 4.3 Porter's Five Forces Analysis

Chapter 5. Global AI in Pathology Market, By Neural Network

• 5.1 Global Convolutional neural networks (CNNs) Market, By Region
• 5.2 Global Generative adversarial networks (GANs) Market, By Region
• 5.3 Global Recurrent neural networks (RNNs) Market, By Region
• 5.4 Global Others Market, By Region

Chapter 6. Global AI in Pathology Market, By Application

• 6.1 Global Drug Discovery Market, By Region
• 6.2 Global Disease Diagnosis & Prognosis Market, By Region
• 6.3 Global Clinical Workflow Market, By Region
• 6.4 Global Others Market, By Region

Chapter 7. Global AI in Pathology Market, By End User

• 7.1 Global Pharmaceutical & Biotechnology Companies Market, By Region
• 7.2 Global Hospitals & Reference Laboratories Market, By Region
• 7.3 Global Academic & Research Institutes Market, By Region

Chapter 8. Global AI in Pathology Market, By Component

• 8.1 Global Scanners Market, By Region
• 8.2 Global Software Market, By Region

Chapter 9. Global AI in Pathology Market, By Region

• 9.1 North America AI in Pathology Market
  • 9.1.1 North America AI in Pathology Market, By Neural Network
    • 9.1.1.1 North America Convolutional neural networks (CNNs) Market, By Country
    • 9.1.1.2 North America Generative adversarial networks (GANs) Market, By Country
    • 9.1.1.3 North America Recurrent neural networks (RNNs) Market, By Country
    • 9.1.1.4 North America Others Market, By Country
  • 9.1.2 North America AI in Pathology Market, By Application
    • 9.1.2.1 North America Drug Discovery Market, By Country
    • 9.1.2.2 North America Disease Diagnosis & Prognosis Market, By Country
    • 9.1.2.3 North America Clinical Workflow Market, By Country
    • 9.1.2.4 North America Others Market, By Country
  • 9.1.3 North America AI in Pathology Market, By End User
    • 9.1.3.1 North America Pharmaceutical & Biotechnology Companies Market, By Country
    • 9.1.3.2 North America Hospitals & Reference Laboratories Market, By Country
    • 9.1.3.3 North America Academic & Research Institutes Market, By Country
  • 9.1.4 North America AI in Pathology Market, By Component
    • 9.1.4.1 North America Scanners Market, By Country
    • 9.1.4.2 North America Software Market, By Country
  • 9.1.5 North America AI in Pathology Market, By Country
    • 9.1.5.1 US AI in Pathology Market
      • 9.1.5.1.1 US AI in Pathology Market, By Neural Network
      • 9.1.5.1.2 US AI in Pathology Market, By Application
      • 9.1.5.1.3 US AI in Pathology Market, By End User
      • 9.1.5.1.4 US AI in Pathology Market, By Component
    • 9.1.5.2 Canada AI in Pathology Market
      • 9.1.5.2.1 Canada AI in Pathology Market, By Neural Network
      • 9.1.5.2.2 Canada AI in Pathology Market, By Application
      • 9.1.5.2.3 Canada AI in Pathology Market, By End User
      • 9.1.5.2.4 Canada AI in Pathology Market, By Component
    • 9.1.5.3 Mexico AI in Pathology Market
      • 9.1.5.3.1 Mexico AI in Pathology Market, By Neural Network
      • 9.1.5.3.2 Mexico AI in Pathology Market, By Application
      • 9.1.5.3.3 Mexico AI in Pathology Market, By End User
      • 9.1.5.3.4 Mexico AI in Pathology Market, By Component
    • 9.1.5.4 Rest of North America AI in Pathology Market
      • 9.1.5.4.1 Rest of North America AI in Pathology Market, By Neural Network
      • 9.1.5.4.2 Rest of North America AI in Pathology Market, By Application
      • 9.1.5.4.3 Rest of North America AI in Pathology Market, By End User
      • 9.1.5.4.4 Rest of North America AI in Pathology Market, By Component
• 9.2 Europe AI in Pathology Market
  • 9.2.1 Europe AI in Pathology Market, By Neural Network
    • 9.2.1.1 Europe Convolutional neural networks (CNNs) Market, By Country
    • 9.2.1.2 Europe Generative adversarial networks (GANs) Market, By Country
    • 9.2.1.3 Europe Recurrent neural networks (RNNs) Market, By Country
    • 9.2.1.4 Europe Others Market, By Country
  • 9.2.2 Europe AI in Pathology Market, By Application
    • 9.2.2.1 Europe Drug Discovery Market, By Country
    • 9.2.2.2 Europe Disease Diagnosis & Prognosis Market, By Country
    • 9.2.2.3 Europe Clinical Workflow Market, By Country
    • 9.2.2.4 Europe Others Market, By Country
  • 9.2.3 Europe AI in Pathology Market, By End User
    • 9.2.3.1 Europe Pharmaceutical & Biotechnology Companies Market, By Country
    • 9.2.3.2 Europe Hospitals & Reference Laboratories Market, By Country
    • 9.2.3.3 Europe Academic & Research Institutes Market, By Country
  • 9.2.4 Europe AI in Pathology Market, By Component
    • 9.2.4.1 Europe Scanners Market, By Country
    • 9.2.4.2 Europe Software Market, By Country
  • 9.2.5 Europe AI in Pathology Market, By Country
    • 9.2.5.1 Germany AI in Pathology Market
      • 9.2.5.1.1 Germany AI in Pathology Market, By Neural Network
      • 9.2.5.1.2 Germany AI in Pathology Market, By Application
      • 9.2.5.1.3 Germany AI in Pathology Market, By End User
      • 9.2.5.1.4 Germany AI in Pathology Market, By Component
    • 9.2.5.2 UK AI in Pathology Market
      • 9.2.5.2.1 UK AI in Pathology Market, By Neural Network
      • 9.2.5.2.2 UK AI in Pathology Market, By Application
      • 9.2.5.2.3 UK AI in Pathology Market, By End User
      • 9.2.5.2.4 UK AI in Pathology Market, By Component
    • 9.2.5.3 France AI in Pathology Market
      • 9.2.5.3.1 France AI in Pathology Market, By Neural Network
      • 9.2.5.3.2 France AI in Pathology Market, By Application
      • 9.2.5.3.3 France AI in Pathology Market, By End User
      • 9.2.5.3.4 France AI in Pathology Market, By Component
    • 9.2.5.4 Russia AI in Pathology Market
      • 9.2.5.4.1 Russia AI in Pathology Market, By Neural Network
      • 9.2.5.4.2 Russia AI in Pathology Market, By Application
      • 9.2.5.4.3 Russia AI in Pathology Market, By End User
      • 9.2.5.4.4 Russia AI in Pathology Market, By Component
    • 9.2.5.5 Spain AI in Pathology Market
      • 9.2.5.5.1 Spain AI in Pathology Market, By Neural Network
      • 9.2.5.5.2 Spain AI in Pathology Market, By Application
      • 9.2.5.5.3 Spain AI in Pathology Market, By End User
      • 9.2.5.5.4 Spain AI in Pathology Market, By Component
    • 9.2.5.6 Italy AI in Pathology Market
      • 9.2.5.6.1 Italy AI in Pathology Market, By Neural Network
      • 9.2.5.6.2 Italy AI in Pathology Market, By Application
      • 9.2.5.6.3 Italy AI in Pathology Market, By End User
      • 9.2.5.6.4 Italy AI in Pathology Market, By Component
    • 9.2.5.7 Rest of Europe AI in Pathology Market
      • 9.2.5.7.1 Rest of Europe AI in Pathology Market, By Neural Network
      • 9.2.5.7.2 Rest of Europe AI in Pathology Market, By Application
      • 9.2.5.7.3 Rest of Europe AI in Pathology Market, By End User
      • 9.2.5.7.4 Rest of Europe AI in Pathology Market, By Component
• 9.3 Asia Pacific AI in Pathology Market
  • 9.3.1 Asia Pacific AI in Pathology Market, By Neural Network
    • 9.3.1.1 Asia Pacific Convolutional neural networks (CNNs) Market, By Country
    • 9.3.1.2 Asia Pacific Generative adversarial networks (GANs) Market, By Country
    • 9.3.1.3 Asia Pacific Recurrent neural networks (RNNs) Market, By Country
    • 9.3.1.4 Asia Pacific Others Market, By Country
  • 9.3.2 Asia Pacific AI in Pathology Market, By Application
    • 9.3.2.1 Asia Pacific Drug Discovery Market, By Country
    • 9.3.2.2 Asia Pacific Disease Diagnosis & Prognosis Market, By Country
    • 9.3.2.3 Asia Pacific Clinical Workflow Market, By Country
    • 9.3.2.4 Asia Pacific Others Market, By Country
  • 9.3.3 Asia Pacific AI in Pathology Market, By End User
    • 9.3.3.1 Asia Pacific Pharmaceutical & Biotechnology Companies Market, By Country
    • 9.3.3.2 Asia Pacific Hospitals & Reference Laboratories Market, By Country
    • 9.3.3.3 Asia Pacific Academic & Research Institutes Market, By Country
  • 9.3.4 Asia Pacific AI in Pathology Market, By Component
    • 9.3.4.1 Asia Pacific Scanners Market, By Country
    • 9.3.4.2 Asia Pacific Software Market, By Country
  • 9.3.5 Asia Pacific AI in Pathology Market, By Country
    • 9.3.5.1 China AI in Pathology Market
      • 9.3.5.1.1 China AI in Pathology Market, By Neural Network
      • 9.3.5.1.2 China AI in Pathology Market, By Application
      • 9.3.5.1.3 China AI in Pathology Market, By End User
      • 9.3.5.1.4 China AI in Pathology Market, By Component
    • 9.3.5.2 Japan AI in Pathology Market
      • 9.3.5.2.1 Japan AI in Pathology Market, By Neural Network
      • 9.3.5.2.2 Japan AI in Pathology Market, By Application
      • 9.3.5.2.3 Japan AI in Pathology Market, By End User
      • 9.3.5.2.4 Japan AI in Pathology Market, By Component
    • 9.3.5.3 India AI in Pathology Market
      • 9.3.5.3.1 India AI in Pathology Market, By Neural Network
      • 9.3.5.3.2 India AI in Pathology Market, By Application
      • 9.3.5.3.3 India AI in Pathology Market, By End User
      • 9.3.5.3.4 India AI in Pathology Market, By Component
    • 9.3.5.4 South Korea AI in Pathology Market
      • 9.3.5.4.1 South Korea AI in Pathology Market, By Neural Network
      • 9.3.5.4.2 South Korea AI in Pathology Market, By Application
      • 9.3.5.4.3 South Korea AI in Pathology Market, By End User
      • 9.3.5.4.4 South Korea AI in Pathology Market, By Component
    • 9.3.5.5 Singapore AI in Pathology Market
      • 9.3.5.5.1 Singapore AI in Pathology Market, By Neural Network
      • 9.3.5.5.2 Singapore AI in Pathology Market, By Application
      • 9.3.5.5.3 Singapore AI in Pathology Market, By End User
      • 9.3.5.5.4 Singapore AI in Pathology Market, By Component
    • 9.3.5.6 Malaysia AI in Pathology Market
      • 9.3.5.6.1 Malaysia AI in Pathology Market, By Neural Network
      • 9.3.5.6.2 Malaysia AI in Pathology Market, By Application
      • 9.3.5.6.3 Malaysia AI in Pathology Market, By End User
      • 9.3.5.6.4 Malaysia AI in Pathology Market, By Component
    • 9.3.5.7 Rest of Asia Pacific AI in Pathology Market
      • 9.3.5.7.1 Rest of Asia Pacific AI in Pathology Market, By Neural Network
      • 9.3.5.7.2 Rest of Asia Pacific AI in Pathology Market, By Application
      • 9.3.5.7.3 Rest of Asia Pacific AI in Pathology Market, By End User
      • 9.3.5.7.4 Rest of Asia Pacific AI in Pathology Market, By Component
• 9.4 LAMEA AI in Pathology Market
  • 9.4.1 LAMEA AI in Pathology Market, By Neural Network
    • 9.4.1.1 LAMEA Convolutional neural networks (CNNs) Market, By Country
    • 9.4.1.2 LAMEA Generative adversarial networks (GANs) Market, By Country
    • 9.4.1.3 LAMEA Recurrent neural networks (RNNs) Market, By Country
    • 9.4.1.4 LAMEA Others Market, By Country
  • 9.4.2 LAMEA AI in Pathology Market, By Application
    • 9.4.2.1 LAMEA Drug Discovery Market, By Country
    • 9.4.2.2 LAMEA Disease Diagnosis & Prognosis Market, By Country
    • 9.4.2.3 LAMEA Clinical Workflow Market, By Country
    • 9.4.2.4 LAMEA Others Market, By Country
  • 9.4.3 LAMEA AI in Pathology Market, By End User
    • 9.4.3.1 LAMEA Pharmaceutical & Biotechnology Companies Market, By Country
    • 9.4.3.2 LAMEA Hospitals & Reference Laboratories Market, By Country
    • 9.4.3.3 LAMEA Academic & Research Institutes Market, By Country
  • 9.4.4 LAMEA AI in Pathology Market, By Component
    • 9.4.4.1 LAMEA Scanners Market, By Country
    • 9.4.4.2 LAMEA Software Market, By Country
  • 9.4.5 LAMEA AI in Pathology Market, By Country
    • 9.4.5.1 Brazil AI in Pathology Market
      • 9.4.5.1.1 Brazil AI in Pathology Market, By Neural Network
      • 9.4.5.1.2 Brazil AI in Pathology Market, By Application
      • 9.4.5.1.3 Brazil AI in Pathology Market, By End User
      • 9.4.5.1.4 Brazil AI in Pathology Market, By Component
    • 9.4.5.2 Argentina AI in Pathology Market
      • 9.4.5.2.1 Argentina AI in Pathology Market, By Neural Network
      • 9.4.5.2.2 Argentina AI in Pathology Market, By Application
      • 9.4.5.2.3 Argentina AI in Pathology Market, By End User
      • 9.4.5.2.4 Argentina AI in Pathology Market, By Component
    • 9.4.5.3 UAE AI in Pathology Market
      • 9.4.5.3.1 UAE AI in Pathology Market, By Neural Network
      • 9.4.5.3.2 UAE AI in Pathology Market, By Application
      • 9.4.5.3.3 UAE AI in Pathology Market, By End User
      • 9.4.5.3.4 UAE AI in Pathology Market, By Component
    • 9.4.5.4 Saudi Arabia AI in Pathology Market
      • 9.4.5.4.1 Saudi Arabia AI in Pathology Market, By Neural Network
      • 9.4.5.4.2 Saudi Arabia AI in Pathology Market, By Application
      • 9.4.5.4.3 Saudi Arabia AI in Pathology Market, By End User
      • 9.4.5.4.4 Saudi Arabia AI in Pathology Market, By Component
    • 9.4.5.5 South Africa AI in Pathology Market
      • 9.4.5.5.1 South Africa AI in Pathology Market, By Neural Network
      • 9.4.5.5.2 South Africa AI in Pathology Market, By Application
      • 9.4.5.5.3 South Africa AI in Pathology Market, By End User
      • 9.4.5.5.4 South Africa AI in Pathology Market, By Component
    • 9.4.5.6 Nigeria AI in Pathology Market
      • 9.4.5.6.1 Nigeria AI in Pathology Market, By Neural Network
      • 9.4.5.6.2 Nigeria AI in Pathology Market, By Application
      • 9.4.5.6.3 Nigeria AI in Pathology Market, By End User
      • 9.4.5.6.4 Nigeria AI in Pathology Market, By Component
    • 9.4.5.7 Rest of LAMEA AI in Pathology Market
      • 9.4.5.7.1 Rest of LAMEA AI in Pathology Market, By Neural Network
      • 9.4.5.7.2 Rest of LAMEA AI in Pathology Market, By Application
      • 9.4.5.7.3 Rest of LAMEA AI in Pathology Market, By End User
      • 9.4.5.7.4 Rest of LAMEA AI in Pathology Market, By Component

Chapter 10. Company Profiles

• 10.1 Koninklijke Philips N.V.
  • 10.1.1 Company Overview
  • 10.1.2 Financial Analysis
  • 10.1.3 Segmental and Regional Analysis
  • 10.1.4 Research & Development Expense
  • 10.1.5 Recent strategies and developments:
    • 10.1.5.1 Product Launches and Product Expansions:
  • 10.1.6 SWOT Analysis
• 10.2 F. Hoffmann-La Roche Ltd.
  • 10.2.1 Company Overview
  • 10.2.2 Financial Analysis
  • 10.2.3 Segmental and Regional Analysis
  • 10.2.4 Research & Development Expense
  • 10.2.5 Recent strategies and developments:
    • 10.2.5.1 Partnerships, Collaborations, and Agreements:
  • 10.2.6 SWOT Analysis
• 10.3 Hologic, Inc.
  • 10.3.1 Company Overview
  • 10.3.2 Financial Analysis
  • 10.3.3 Segmental and Regional Analysis
  • 10.3.4 Research & Development Expenses
  • 10.3.5 Recent strategies and developments:
    • 10.3.5.1 Partnerships, Collaborations, and Agreements:
    • 10.3.5.2 Product Launches and Product Expansions:
  • 10.3.6 SWOT Analysis
• 10.4 Visiopharm A/S
  • 10.4.1 Company Overview
  • 10.4.2 Recent strategies and developments:
    • 10.4.2.1 Partnerships, Collaborations, and Agreements:
  • 10.4.3 SWOT Analysis
• 10.5 Paige AI, Inc.
  • 10.5.1 Company Overview
  • 10.5.2 Recent strategies and developments:
    • 10.5.2.1 Partnerships, Collaborations, and Agreements:
    • 10.5.2.2 Product Launches and Product Expansions:
  • 10.5.3 SWOT Analysis
• 10.6 PathAI, Inc.
  • 10.6.1 Company Overview
  • 10.6.2 Recent strategies and developments:
    • 10.6.2.1 Partnerships, Collaborations, and Agreements:
  • 10.6.3 SWOT Analysis
• 10.7 Aiforia Technologies Plc
  • 10.7.1 Company Overview
  • 10.7.2 Financial Analysis
  • 10.7.3 Recent strategies and developments:
    • 10.7.3.1 Partnerships, Collaborations, and Agreements:
  • 10.7.4 SWOT Analysis
• 10.8 Indica Labs, Inc.
  • 10.8.1 Company Overview
  • 10.8.2 Recent strategies and developments:
    • 10.8.2.1 Partnerships, Collaborations, and Agreements:
  • 10.8.3 SWOT Analysis
• 10.9 Optrascan, Inc. (Optra Ventures, LLC)
  • 10.9.1 Company Overview
  • 10.9.2 Recent strategies and developments:
    • 10.9.2.1 Partnerships, Collaborations, and Agreements:
    • 10.9.2.2 Product Launches and Product Expansions:
  • 10.9.3 SWOT Analysis
• 10.10. MindPeak GmbH
  • 10.10.1 Company Overview
  • 10.10.2 Recent strategies and developments:
    • 10.10.2.1 Partnerships, Collaborations, and Agreements:
  • 10.10.3 SWOT Analysis

Chapter 11. Winning imperatives of AI in Pathology Market