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Global AI-based Digital Pathology/AI Pathology Market Research Report 2022-2035 Featuring Profiles of PathAI, Paige, Akoya Biosciences, PROSCIA, Visiopharm, Roche, Aiforia, Indica Labs, & Ibex

Global AI-based Digital Pathology/AI Pathology Market Research Report 2022-2035 Featuring Profiles of PathAI, Paige, Akoya Biosciences, PROSCIA, Visiopharm, Roche, Aiforia, Indica Labs, & Ibex

2022-2035 年全球基于人工智能的数字病理学/人工智能病理学市场研究报告收录了 Pathai、Paige、Akoya Biosciences、PROSCIA、Visiopharm、Roche、Aiforia、Indica Labs 和 Ibex 的简介
PR Newswire ·  2023/01/21 15:20

DUBLIN, Jan. 21, 2023 /PRNewswire/ -- The "AI-based Digital Pathology/AI Pathology Market Distribution by Type of Neural Network, Type of Assay, Type of End-user, Area of Application, Type of Target Disease Indication and Key Geographies, 2022-2035" report has been added to  ResearchAndMarkets.com's offering.

都柏林2023年1月21日 /PRNewswire/ — “2022-2035 年按神经网络类型、检测类型、最终用户类型、应用领域、目标疾病适应症类型和关键地区划分的基于人工智能的数字病理学/人工智能病理学市场分布” 报告已添加到 ResearchandMarkets.co 提供。

The "AI-based Digital Pathology / AI Pathology Market" report features an extensive study of the current market landscape and future potential of the AI-based digital pathology market. The study features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in providing AI-based digital pathology.

“基于人工智能的数字病理学/人工智能病理学市场” 报告对基于人工智能的数字病理学市场的当前市场格局和未来潜力进行了广泛研究。该研究以深入分析为特色,重点介绍了参与提供基于人工智能的数字病理学的各利益相关者的能力。

Amidst the ever-growing demand for pathology services, the simultaneous use of technological advances to automate and digitize healthcare procedures is growing. These developments have accelerated research and clinical diagnosis, as well as enhanced patient outcomes, in the recent years.

在病理学服务需求不断增长的背景下,同时使用技术进步实现医疗程序自动化和数字化的现象正在增长。近年来,这些进展加速了研究和临床诊断,并改善了患者的预后。

Specifically, AI-powered digital imaging is one such technology, which has revolutionized the pathology industry by enabling high-throughput scanning of patient samples. To provide more context, AI-based digital pathology / AI pathology involves collection, management, analyzing and sharing of data (via digital slides) in a digital setting.

具体而言,人工智能驱动的数字成像就是这样一种技术,它通过实现患者样本的高通量扫描,彻底改变了病理学行业。为了提供更多背景信息,基于人工智能的数字病理学/人工智能病理学涉及在数字环境中收集、管理、分析和共享数据(通过数字幻灯片)。

Through this process, digital slides are created by scanning conventional glass slides with a scanning device, which may be seen on a computer screen or a mobile device and offer a high-resolution digital image. Further, AI pathology technique presents a viable solution to managing the growing pathology workload, while also ensuring more rapid and consistent diagnostic services and research activities.

通过此过程,数字幻灯片是通过使用扫描设备扫描传统的玻璃幻灯片来创建的,这些幻灯片可以在计算机屏幕或移动设备上看到,并提供高分辨率的数字图像。此外,人工智能病理学技术为管理不断增长的病理学工作量提供了可行的解决方案,同时还确保了更快、更一致的诊断服务和研究活动。

Moreover, AI-powered digital pathology solutions (digital pathology scanners and digital pathology software) allow pathologists to examine more cases and offer a precise diagnosis. It is worth highlighting that digitized workflows can speed up processing times, lower administrative errors, enable remote collaboration and boost productivity, thereby, allowing significant cost savings.

此外,人工智能驱动的数字病理学解决方案(数字病理扫描仪和数字病理学软件)使病理学家能够检查更多病例并提供精确的诊断。值得强调的是,数字化工作流程可以加快处理时间,减少管理错误,实现远程协作并提高生产力,从而节省大量成本。

Considering the rising popularity and demand for such solutions in the healthcare and research industry, and the ongoing efforts of AI-powered digital pathology solution providers / AI pathology solution providers to further improve / expand their respective portfolios, we believe that the AI-based digital pathology market is likely to evolve at a steady pace, till 2035.

考虑到医疗保健和研究行业对此类解决方案的受欢迎程度和需求日益增加,以及人工智能驱动的数字病理学解决方案提供商/人工智能病理学解决方案提供商为进一步改善/扩大各自产品组合所做的持续努力,我们认为,在2035年之前,基于人工智能的数字病理学市场可能会稳步发展。

Scope of the Report

报告的范围

  • An executive summary of the insights captured during our research. It offers a high-level view on the current state of AI-based digital pathology market and its likely evolution in the mid-long term.
  • A general introduction to AI-based digital pathology, featuring information on artificial intelligence in digital pathology, workflow of AI-based digital pathology, applications of AI-based digital pathology solutions in the healthcare domain.
  • A detailed assessment of the overall market landscape of AI-based digital pathology providers, based on several relevant parameters.
  • An in-depth analysis, highlighting the contemporary market trends.
  • Elaborate profiles of various prominent players that are engaged in offering services related to AI-based digital pathology. Each profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and management team) and details related to recent developments and an informed future outlook.
  • A company competitive analysis of various players engaged in this domain. It highlights the capabilities of industry players (in terms of their expertise across various services related to AI-based digital pathology).
  • An analysis of the funding and investments made within this domain, during the period 2016-2022, based on several relevant parameters, such as number of instances, amount invested, type of funding, area of application, geography and information on most active players engaged in the AI-based digital pathology domain.
  • An elaborate analysis in order to estimate the current and future demand for AI-based digital pathology, based on several relevant parameters.
  • A detailed market forecast analysis, highlighting the likely evolution of the AI-based digital pathology market in the short to mid-term and long term, over the period 2022-2035. In order to account for future uncertainties and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, which represent different tracks of the industry's growth.
  • 研究期间获得的见解的执行摘要。它对基于人工智能的数字病理学市场的现状及其在中长期内的可能演变提供了高层次的看法。
  • 基于人工智能的数字病理学概述,重点介绍数字病理学中的人工智能、基于人工智能的数字病理学工作流程、基于人工智能的数字病理学解决方案在医疗保健领域的应用。
  • 根据多个相关参数,对基于人工智能的数字病理学提供商的整体市场格局进行详细评估。
  • 深入分析,重点介绍当代市场趋势。
  • 详细介绍参与提供与基于人工智能的数字病理学相关的服务的各种知名参与者。每份简介都简要概述了公司(包括有关成立年份、员工人数、总部地点和管理团队的信息),以及与最新发展和明智的未来展望相关的详细信息。
  • 公司对从事该领域的各种参与者的竞争分析。它强调了行业参与者的能力(就他们在与基于人工智能的数字病理学相关的各种服务方面的专业知识而言)。
  • 根据多个相关参数,例如实例数量、投资金额、资金类型、应用领域、地理位置以及参与基于人工智能的数字病理学领域的最活跃参与者的信息,分析了2016-2022年期间在该领域进行的资金和投资。
  • 一项详尽的分析,旨在根据几个相关参数估算当前和未来对基于人工智能的数字病理学的需求。
  • 详细的市场预测分析,重点介绍了基于人工智能的数字病理学市场在2022-2035年期间在短期至中期和长期内可能的演变。为了考虑未来的不确定性并增加我们模型的稳健性,我们提供了三种市场预测情景,即保守情景、基本情景和乐观情景,它们代表了行业增长的不同轨迹。

Frequently Asked Questions

经常问的问题

  • Who are the leading players engaged in offering AI-based digital pathology / AI pathology in the healthcare domain?
  • Which geographies emerged as key hubs for AI-based digital pathology providers?
  • Which type of end-users are primarily employing AI in digital pathology in their regular workflow?
  • What type of funding initiatives are most commonly being reported by stakeholders in this domain?
  • What are the key strategies that can be implemented by emerging players to enter the AI-based digital pathology market?
  • What are the key market trends and driving factors that are likely to impact the growth of the AI-based digital pathology / AI pathology market?
  • How is the current and future opportunity likely to be distributed across key market segment?
  • 在医疗保健领域提供基于人工智能的数字病理学/人工智能病理学的主要参与者有哪些?
  • 哪些地区成为基于人工智能的数字病理学提供者的关键中心?
  • 哪类最终用户在常规工作流程中主要在数字病理学中使用 AI?
  • 该领域的利益相关者最常报告哪种类型的融资举措?
  • 新兴参与者可以实施哪些关键策略来进入基于人工智能的数字病理学市场?
  • 可能影响基于人工智能的数字病理学/人工智能病理学市场增长的关键市场趋势和驱动因素有哪些?
  • 当前和未来的机会在关键细分市场中可能如何分配?

Key Topics Covered:

涵盖的关键主题:

1. PREFACE
1.1. Chapter Overview
1.2. Market Segmentations
1.3. Research Methodology
1.4. Key Questions Answered
1.5. Chapter Outlines

1。序言
1.1。章节概述
1.2。细分市场
1.3。研究方法论
1.4。关键问题已回答
1.5。章节大纲

2. EXECUTIVE SUMMARY

2。执行摘要

3. INTRODUCTION
3.1. Chapter Overview
3.2. Artificial Intelligence in Digital Pathology
3.3. Workflow of AI-based Digital Pathology
3.4. Applications of AI-based Digital Pathology Solutions
3.5. Regulatory Requirements Focused on AI-based Digital Pathology:
3.6. Challenges Associated with the Use of AI in Digital Pathology
3.7. Future Perspectives

3。导言
3.1。章节概述
3.2。数字病理学中的人工智能
3.3。基于人工智能的数字病理学工作流程
3.4。基于人工智能的数字病理学解决方案的应用
3.5。监管要求侧重于基于人工智能的数字病理学:
3.6。与在数字病理学中使用人工智能相关的挑战
3.7。未来展望

4. AI-BASED DIGITAL PATHOLOGY: MARKET LANDSCAPE
4.1. Chapter Overview
4.2. AI-based Digital Pathology Providers: Overall Market Landscape
4.3. AI-based Digital Pathology Providers: Developer Landscape

4。基于人工智能的数字病理学:市场格局
4.1。章节概述
4.2。基于人工智能的数字病理学提供商:整体市场格局
4.3。基于人工智能的数字病理学提供商:开发者格局

5. AI-BASED DIGITAL PATHOLOGY MARKET: KEY INSIGHTS
5.1. Chapter Overview
5.1.1. Analysis by Type of Service and Area of Application
5.1.2. Analysis by Type of Feature and Area of Application
5.1.3. Analysis by Type of Product and Area of Application
5.1.4. Analysis by Type of Product and Location of Headquarters
5.1.5. Analysis by Company Size and Location of Headquarters

5。基于人工智能的数字病理学市场:关键见解
5.1。章节概述
5.1.1。按服务类型和应用领域进行分析
5.1.2。按功能类型和应用领域进行分析
5.1.3。按产品类型和应用领域进行分析
5.1.4。按产品类型和总部位置进行分析
5.1.5。按公司规模和总部位置进行分析

6. COMPANY PROFILES
6.1. Chapter Overview
6.2. PathAI
6.2.1. Company Overview
6.2.2. Recent Developments and Future Outlook
6.3. Paige
6.4. Akoya Biosciences
6.5. PROSCIA
6.6. Visiopharm
6.7. Roche Tissue Diagnostics
6.8. Aiforia Technologies
6.9. Indica Labs
6.10. Ibex Medical Analytics

6。公司简介
6.1。章节概述
6.2。Pathai
6.2.1。公司概述
6.2.2。最新发展和未来展望
6.3。Paige
6.4。Akoya 生物科学
6.5。普罗西亚
6.6。Visipharm
6.7。罗氏组织诊断
6.8。Aiforia 科技
6.9。 Indica Labs
6.10。Ibex 医学分析

7. COMPANY COMPETITIVENESS ANALYSIS
7.1. Chapter Overview
7.2. Assumptions and Key Parameters
7.3. Methodology
7.4. Benchmarking of Portfolio Strength
7.5. Benchmarking of Funding Strength
7.6. Company Competitiveness Analysis: Small Players
7.7. Company Competitiveness Analysis: Mid-sized Players
7.8. Company Competitiveness Analysis: Large Players

7。公司竞争力分析
7.1。章节概述
7.2。假设和关键参数
7.3。方法论
7.4。对投资组合实力进行基准测试
7.5。设定资金实力的基准
7.6。公司竞争力分析:小企业
7.7。公司竞争力分析:中型企业
7.8。公司竞争力分析:大型企业

8. FUNDING AND INVESTMENTS
8.1. Chapter Overview
8.2. Types of Funding
8.3. AI-based Digital Pathology: List of Funding and Investments
8.4. Concluding Remarks

8。资金和投资
8.1。章节概述
8.2。资金类型
8.3。基于人工智能的数字病理学:资金和投资清单
8.4。结束语

9. DEMAND ANALYSIS
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Global Demand for AI-based Digital Pathology, 2022-2035
9.4. Demand for AI-based Digital Pathology: Analysis by Geography
9.5. Demand for AI-based Digital Pathology: Analysis by Type of End-user
9.6. Concluding Remarks

9。需求分析
9.1。章节概述
9.2。范围和方法
9.3。2022-2035 年全球对基于人工智能的数字病理学的需求
9.4。对基于人工智能的数字病理学的需求:地理分析
9.5。对基于人工智能的数字病理学的需求:按最终用户类型进行分析
9.6。结束语

10. MARKET SIZING AND OPPORTUNITY ANALYSIS
10.1. Chapter Overview
10.2. Forecast Methodology and Key Assumptions
10.3. Global AI-based Digital Pathology Market, 2022-2035
10.4. AI-based Digital Pathology Market: Analysis by Type of Neural Network, 2022 and 2035
10.5. AI-based Digital Pathology Market: Analysis by Type of Assay, 2022 and 2035
10.6. AI-based Digital Pathology Market: Analysis by Type of End-user, 2022 and 2035
10.7. AI-based Digital Pathology Market: Analysis by Area of Application, 2022 and 2035
10.8. AI-based Digital Pathology Market: Analysis by Target Disease Indication, 2022 and 2035
10.9. AI-based Digital Pathology Market: Analysis by Key Geographies, 2022 and 2035

10。市场规模和机会分析
10.1。章节概述
10.2。预测方法和关键假设
10.3。2022-2035 年全球基于人工智能的数字病理学市场
10.4。基于人工智能的数字病理学市场:2022年和2035年按神经网络类型划分的分析
10.5。基于人工智能的数字病理学市场:2022年和2035年按检测类型划分的分析
10.6。基于人工智能的数字病理学市场:2022年和2035年按最终用户类型进行分析
10.7。基于人工智能的数字病理学市场:2022年和2035年按应用领域划分的分析
10.8。基于人工智能的数字病理学市场:2022年和2035年按目标疾病适应症划分的分析
10.9。基于人工智能的数字病理学市场:2022年和2035年按关键地区划分的分析

11. CONCLUDING REMARKS

11。结论性意见

12. EXECUTIVE INSIGHTS
12.1. Chapter Overview
12.2. aetherAIInterview Transcript: Joe Yeh (Chief Executive Officer and Chairman)
12.3. CTL Clinitech LabInterview Transcript: Suraj Bramhane (Laboratory Director and Chief Pathologist)
12.4. Huron Digital Pathology Interview Transcript: Savvas Damaskinos (Vice President, Research and Technology)
12.5. Mindpeak Interview Transcript: Anil Berger (Vice President, Sales and Marketing)
12.6. PramanaInterview Transcript: Scott Wallace (Vice President, Business Development and Strategic Partnerships)

12。高管见解
12.1。章节概述
12.2. Aetherai 访谈记录: Joe Yeh (首席执行官兼董事长)
12.3。CTL Clinitech Lab访谈记录:Suraj Bramhane(实验室主任兼首席病理学家)
12.4。休伦数字病理学访谈记录: 萨瓦斯·达马斯基诺斯 (研究与技术副总裁)
12.5。Mindpeak 访谈记录:Anil Berger(销售和营销副总裁)
12.6。Pramana 访谈记录: 斯科特·华莱士 (业务发展和战略合作伙伴关系副总裁)

13. APPENDIX 1: TABULATED DATA

13。附录 1:表格数据

14. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATION

14。附录 2: 公司和组织名单

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