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放射学报告产生中人工智慧的全球市场：预测（2023-2028）
市场调查报告书
商品编码
1410142

放射学报告产生中人工智慧的全球市场：预测（2023-2028）

AI in Radiology Report Generation Market - Forecasts from 2023 to 2028
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 140 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

全球放射学报告人工智慧市场规模预计在预测期内将以 33.98% 的复合年增长率成长。

人工智慧在医疗保健领域的变革力量正在改变放射学报告的人工智慧市场。人工智慧演算法与核医影像设备无缝集成，以前所未有的精度和速度分析和解释医学影像。这项突破性技术可自动产生报告、提高工作效率并减少放射科医生的工作量。人工智慧产生的报告高度准确，能够及早发现异常情况并更好地治疗患者。此外，人工智慧技术加快了放射科医生的工作流程，使他们能够专注于更困难的情况。随着对快速、准确诊断的需求不断增长，放射学报告市场中的人工智慧有望成为游戏规则的改变者，提供更好的患者治疗结果并简化医疗保健业务，以实现更有效率、更有效的未来。事实证明确实如此。

医学影像资料量的增加推动放射学报告产生的人工智慧市场成长

医学影像资料量的不断增加是放射学报告产生领域人工智慧市场的主要驱动力。随着医疗机构和组织使用数位成像技术，创建的医学影像数量呈指数级增长。这些海量资料由 X 光、MRI、 电脑断层扫描和其他诊断工具组成，形成了一个庞大的关键诊断资讯库。手动分析如此大量的照片非常耗时，而且容易出现人为错误。深度学习演算法尤其擅长以惊人的速度和准确性处理和解释此类资料。人工智慧演算法可以快速分析并从这些照片中提取关键讯息，帮助放射科医生快速产生完整、准确的报告。人工智慧更好地处理大量资料的能力加速了其在放射学领域的接受度，并显着改善了医疗结果。

放射学报告创建的人工智慧市场对自动报告创建的需求不断增长

对更高效率、准确性和工作流程优化的需求正在推动放射学报告人工智慧市场对自动报告产生的需求不断增长。传统的手动报告产生过程非常耗时且容易出现人为错误，这可能会导致患者照护的延迟。采用人工智慧演算法的自动化简化了报告生成流程，显着缩短了周转时间并提高了整体放射学效率。透过利用最新的自然语言处理 (NLP) 和影像识别演算法，人工智慧系统可以评估医学影像、提取相关资讯并提供完整、标准化的报告。这不仅节省了放射科医生的时间，而且还确保了统一和准确的报告，支持改善患者照护，并实现医疗专业人员之间的快速沟通。随着医疗保健组织努力改善诊断和患者治疗结果，对自动化报告的需求不断增长。

人工智慧开拓与医疗机构的合作扩大了放射学报告中人工智慧的市场规模

在放射学报告的人工智慧市场中，人工智慧开发者和医疗机构之间的合作变得越来越重要。人工智慧开发人员在设计复杂演算法方面的独特经验，与医疗保健组织的深入主题知识相结合，提供了巨大的协同效应。医疗机构拥有庞大的医疗资料库和真实的临床资料，可用于训练和检验人工智慧演算法。同时，人工智慧开发人员正在提供尖端工具和处理资源，以快速处理和分析大量医疗图像资料。此类合作将有助于加速人工智慧驱动的放射学报告技术的开发和实施，鼓励创新并提高诊断准确性。与医学专家密切合作，使人工智慧解决方案能够响应临床需求并解决特定问题，从而改善患者照护并优化放射学工作流程。

北美是放射学报告领域人工智慧的市场领导者

北美被公认为放射学报告领域人工智慧的市场领导者。这是由于该地区强大的基础设施、卓越的医疗保健系统以及在人工智慧技术上的大量支出。世界一流的医学研究机构、科技公司的存在，以及医疗提供者与人工智慧研究人员和开发人员之间的合作，正在加速人工智慧在放射学领域的应用。此外，有利的法律规范和对将人工智慧融入医疗保健流程的重视正在支持北美在推动放射学报告系统的人工智慧改进方面发挥领导作用。因此，放射学报告生成领域的人工智慧市场随着时间的推移正在显着扩大。

在人工智慧市场中采用远端医疗和远端医疗解决方案进行放射学报告。

远端医疗和远端医疗解决方案的普及是放射学报告市场人工智慧的主要驱动力。远端医疗允许医疗保健专业人员与远端位置的患者进行通信，并实现医疗资讯和诊断成像资料的交换。人工智慧驱动的放射学报告解决方案在此类环境中至关重要，因为它们可以有效分析医学影像并即时提供正确的报告。将人工智慧应用于远端医疗将改善放射服务的可近性，特别是在农村和服务不足的地区，并实现更快、更有效的诊断和治疗计划。此外，人工智慧驱动的远端医疗解决方案可以消除面对面咨询的需要，并实现医疗保健提供者之间的无缝协作。随着远端医疗在世界各地变得普及，在放射学报告中引入人工智慧预计将进一步改变医疗保健服务。

主要进展：

  • 2023 年6 月，Aidoc 宣布与Ochsner Health 建立突破性的合作伙伴关係，Ochsner Health 是一家总部位于新奥尔良的领先医疗保健组织，在墨西哥湾南部运营着46 家医院和370 多个医疗和紧急护理中心。此次合作将 Ochsner 的临床人才与 Aidoc 先进的人工智慧技术的力量相结合，以改善路易斯安那州和全部区域的医疗保健提供、体验和优化方式。
  • 2022 年 8 月，领先的医疗保健资讯科技公司 Enlitic Inc. 宣布与 GE Healthcare (GE) 建立新的长期合作关係，以提高业务效率并造福GE 在全球范围内的放射科医生和患者，改善您的治疗结果。 GE 将把 Enlitic 专有的基于人工智慧的 Curie 平台整合到 GE 的放射科医生工作流程中，以促进资料标准化并提高系统效率和容量。
  • 2021年11月，以色列影像处理公司Nanox以约1.1亿美元股票完成与Zebra Medical Vision（现更名为Nanox.AI）的合併，并宣布可能追加8,400万美元股权。

公司产品

  • Watson Imaging AI： IBM Watson Health 提供人工智慧驱动的影像分析功能，帮助放射科医师更准确、更有效地分析医学影像。 Watson Imaging AI 平台使用深度学习演算法来分析 X 光、MRI 和电脑断层扫描等放射影像，以识别潜在的异常并建立完整的报告。
  • Nuance PowerScribe One： PowerScribe One 是一个使用 AI 和自然语言处理 (NLP) 建立放射学报告的完整平台。该平台与核医影像设备结合，利用人工智慧演算法分析医学影像，撷取关键资料，并自动提供完整、准确的报告。
  • Enlitic AI 平台： Enlitic 建立了强大的 AI 平台，用于分析 X 光、 电脑断层扫描和 MRI 等医学影像。该公司的技术使深度学习演算法来帮助放射科医生更准确、更快速地检测和诊断许多医疗状况。
  • Zebra AI1(TM) 分析平台： Zebra Medical Vision 建构了创新的人工智慧分析平台，用于分析医学影像资料并提供完整的放射学报告。深度学习演算法已用于分析多种显像模式，包括电脑断层扫描、X 光和乳房 X 光检查，使放射科医生能够更准确地检测和诊断医疗状况。

目录

第一章简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表

第二章调查方法

  • 调查资料
  • 资讯来源
  • 研究设计

第三章执行摘要

  • 研究亮点

第四章市场动态

  • 市场驱动因素
  • 市场抑制因素
  • 波特五力分析
    • 供应商的议价能力
    • 买方议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 业内竞争对手之间的对抗关係
  • 产业价值链分析

第五章放射学报告创建中的人工智慧市场：按技术分类

  • 介绍
  • 自然语言处理（NLP）
  • 机器学习
  • 深度学习
  • 电脑视觉
  • 其他的

第六章 辐射报告创建中的人工智慧市场：按应用分类

  • 介绍
  • 建立 MRI 扫描报告
  • 电脑断层扫描报告的创建
  • X射线报告的创建
  • 建立超音波报告
  • 建立乳房X光检查报告
  • 其他的

第 7 章放射学报告创建中的人工智慧市场：按最终用户划分

  • 介绍
  • 医院和诊所
  • 影像诊断中心
  • 研究所和学术中心
  • 其他的

第八章辐射报告创建中的人工智慧市场：按地区

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他的
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 其他的
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 其他的
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 韩国
    • 印尼
    • 台湾
    • 其他的

第九章竞争环境及分析

  • 主要企业及策略分析
  • 新兴企业和市场盈利
  • 併购/协议/合作
  • 供应商竞争力矩阵

第十章 公司简介

  • AIDOC MEDICAL LTD.
  • ENLITIC, INC.
  • NUANCE COMMUNICATIONS, INC.
  • SIEMENS HEALTHINEERS AG
  • GE HEALTHCARE（A DIVISION OF GENERAL ELECTRIC COMPANY）
  • ZEBRA MEDICAL VISION LTD.
  • AGFA-GEVAERT GROUP
  • IBM WATSON HEALTH（A DIVISION OF IBM CORPORATION）
  • MCKESSON CORPORATION
  • CUREMETRIX, INC.
简介目录
Product Code: KSI061615806

The AI in radiology report generation market is estimated to grow at a CAGR of 33.98% during the forecast period.

The AI in radiology report generation market has been transformed by AI's transformational powers in healthcare. AI algorithms analyse and interpret medical pictures with unprecedented precision and speed by seamlessly integrating with radiological imaging equipment. This game-changing technology automates report production, increasing productivity and decreasing radiologists' workload. The AI-generated reports are extremely accurate, allowing for earlier detection of irregularities and better patient treatment. Furthermore, AI-powered technologies speed up radiologists' workflow, allowing them to focus on more difficult situations. As the need for quick and precise diagnoses develops, AI in radiology report generation market has shown to be a game changer, offering better patient outcomes and simplifying healthcare operations for a more efficient and effective future.

Increasing Volume of Medical Imaging Data Enhances the AI in Radiology Report Generation Market Growth.

The growing volume of medical imaging data is a major driving force in the AI in radiology report generation market. The volume of medical pictures created has increased tremendously as medical facilities and healthcare organisations use digital imaging technologies. This flood of data comprises X-rays, MRIs, CT scans, and other diagnostic tools, resulting in a large library of vital diagnostic information. Manually analysing such a large number of photos can be time-consuming and prone to human error. Deep learning algorithms, in particular, excel in processing and interpreting such data at unparalleled speed and precision. AI algorithms can swiftly analyse and extract significant information from these pictures, assisting radiologists in fast producing thorough and exact reports. The capacity of AI to successfully handle this data flood has accelerated its acceptance in the radiology area, greatly improving healthcare results.

Rising Demand for Automated Report Generation in AI in Radiology Report Generation Market.

The need for greater efficiency, accuracy, and workflow optimisation is driving the growing demand for automated report generating in the AI in radiology report generating market. Traditional manual report-generating procedures can be time-consuming and prone to human mistakes, potentially resulting in patient care delays. Automation with AI-powered algorithms streamlines the report-generating process, drastically cutting turnaround times and enhancing radiology departments' overall efficiency. AI systems can evaluate medical pictures and extract pertinent information to provide complete and standardised reports by utilising modern natural language processing (NLP) and image recognition algorithms. This not only saves radiologists time but also assures uniform and accurate reporting, supporting improved patient care and allowing prompt communication among healthcare professionals. The need for automated report production continues to rise as healthcare institutions strive for better diagnosis and patient outcomes.

Collaborations between AI Developers and Healthcare Institutions Boost the AI in Radiology Report Generation Market Size.

Collaborations between AI developers and healthcare institutions are becoming increasingly important in the AI in radiology report generation market. AI developers' unique experience in designing complex algorithms, combined with healthcare institutions' in-depth topic knowledge, results in tremendous synergy. Healthcare facilities include enormous medical databases and real-world clinical data that may be used to train and validate AI algorithms. AI developers, on the other hand, contribute cutting-edge tools and processing resources to rapidly handle and analyse massive volumes of medical imaging data. These collaborations help to speed the development and implementation of AI-powered radiology report generating technologies, while also encouraging innovation and boosting diagnostic accuracy. Working closely with healthcare professionals also ensures that AI solutions correspond with clinical requirements and handle specific difficulties, resulting in improved patient care and optimised radiology workflows.

North America is the Market Leader in the AI in Radiology Report Generation Market.

North America was regarded as the market leader in the AI in radiology report generation market. This is due to the region's robust infrastructure, superior healthcare systems, and substantial expenditures in artificial intelligence technology. The existence of world-class medical research institutes, technology firms, and cooperation between healthcare providers and AI developers has accelerated the implementation of AI in radiology practices. Furthermore, favourable regulatory frameworks and an emphasis on integrating AI into healthcare processes have aided North America's leadership in pushing improvements in AI-powered radiology report production systems. So, AI in radiology report generation market is significantly expanding over time.

Adoption of Telemedicine and Remote Healthcare Solutions in AI in Radiology Report Generation Market.

The widespread use of telemedicine and remote healthcare solutions has been a major driving force in the AI in radiology report generation market. Telemedicine enables healthcare practitioners to communicate with patients at a distance, allowing the interchange of medical information and diagnostic imaging data. AI-powered radiology report creation solutions are critical in this setting because they effectively analyse medical pictures and provide correct reports in real time. The application of AI in telemedicine improves radiological service accessibility, particularly in rural or underserved locations, and enables rapid and effective diagnosis and treatment planning. Furthermore, AI-powered remote healthcare solutions eliminate the need for in-person consultations and enable seamless cooperation among healthcare providers. As telemedicine gains popularity throughout the world, the incorporation of AI in radiology report generation is projected to further revolutionise healthcare delivery.

Key Developments:

  • In June 2023, Aidoc announced a groundbreaking alliance with Ochsner Health, a big healthcare organisation based in New Orleans that operates 46 hospitals and over 370 health and urgent care centres throughout the Gulf South. This collaboration combines Ochsner's clinical brilliance with the power of Aidoc's sophisticated AI technologies, resulting in an alliance that improves the way healthcare is given, experienced, and optimised throughout Louisiana and the Gulf South area.
  • In August 2022, Enlitic Inc., a leading healthcare information technology firm, announced a new long-term relationship with GE Healthcare (GE) to improve operational efficiency and results for GE's radiologists and patients worldwide. GE will integrate Enlitic's proprietary AI-based Curie platform into GE radiologist workflows to promote data standardisation and drive system efficiency and capacity.
  • In November 2021, Nanox, an Israeli imaging business, announced the completion of its merger with Zebra Medical Vision, now renamed as Nanox.AI, for about $110 million in stock, with the potential for an additional $84 million in shares dependent on performance.

Company Products:

  • Watson Imaging AI: IBM Watson Health offers image analysis capabilities driven by AI to help radiologists analyse medical pictures more correctly and effectively. Deep learning algorithms were used by the Watson Imaging AI platform to analyse radiological images including as X-rays, MRIs, and CT scans in order to identify probable anomalies and create complete reports.
  • Nuance PowerScribe One: PowerScribe One was a complete platform that used AI and natural language processing (NLP) to generate radiology reports. The platform was coupled with radiological imaging equipment, and AI algorithms were utilised to analyse medical pictures, extract key data, and provide thorough and accurate reports automatically.
  • Enlitic AI Platform: Enlitic created a powerful AI platform for analysing medical pictures such as X-rays, CT scans, and MRIs. Their technology uses deep learning algorithms to help radiologists discover and diagnose numerous medical disorders more accurately and quickly.
  • Zebra AI1™ Analytics Platform: Zebra Medical Vision created an innovative artificial intelligence analytics platform to analyse medical imaging data and provide complete radiology reports. Deep learning algorithms were used to analyse numerous imaging modalities, such as CT scans, X-rays, and mammograms, enabling radiologists to detect and diagnose medical disorders more correctly.

Segmentation:

By Technology

  • Natural Language Processing (Nlp)
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Others

By Application

  • MRI Scan Report Generation
  • CT Scan Report Generation
  • X-Ray Report Generation
  • Ultrasound Report Generation
  • Mammography Report Generation
  • Others

By End-User

  • Hospitals And Clinics
  • Diagnostic Imaging Centers
  • Research Institutes And Academic Centers
  • Others

By Geography

  • North America
  • United States
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • Japan
  • China
  • India
  • South Korea
  • Indonesia
  • Taiwan
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY

  • 2.1. Research Data
  • 2.2. Sources
  • 2.3. Research Design

3. EXECUTIVE SUMMARY

  • 3.1. Research Highlights

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porters Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis

5. AI IN RADIOLOGY REPORT GENERATION MARKET, BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. NATURAL LANGUAGE PROCESSING (NLP)
  • 5.3. MACHINE LEARNING
  • 5.4. DEEP LEARNING
  • 5.5. COMPUTER VISION
  • 5.6. OTHERS

6. AI IN RADIOLOGY REPORT GENERATION MARKET, BY APPLICATION

  • 6.1. Introduction
  • 6.2. MRI SCAN REPORT GENERATION
  • 6.3. CT SCAN REPORT GENERATION
  • 6.4. X-RAY REPORT GENERATION
  • 6.5. ULTRASOUND REPORT GENERATION
  • 6.6. MAMMOGRAPHY REPORT GENERATION
  • 6.7. OTHERS

7. AI IN RADIOLOGY REPORT GENERATION MARKET, BY END-USER

  • 7.1. Introduction
  • 7.2. HOSPITALS AND CLINICS
  • 7.3. DIAGNOSTIC IMAGING CENTERS
  • 7.4. RESEARCH INSTITUTES AND ACADEMIC CENTERS
  • 7.5. OTHERS
  • 7.6. AI IN RADIOLOGY REPORT GENERATION MARKET, BY GEOGRAPHY
  • 7.7. Introduction
  • 7.8. North America
    • 7.8.1. United States
    • 7.8.2. Canada
    • 7.8.3. Mexico
  • 7.9. South America
    • 7.9.1. Brazil
    • 7.9.2. Argentina
    • 7.9.3. Others
  • 7.10. Europe
    • 7.10.1. United Kingdom
    • 7.10.2. Germany
    • 7.10.3. France
    • 7.10.4. Italy
    • 7.10.5. Spain
    • 7.10.6. Others
  • 7.11. Middle East and Africa
    • 7.11.1. Saudi Arabia
    • 7.11.2. UAE
    • 7.11.3. Others
  • 7.12. Asia Pacific
    • 7.12.1. Japan
    • 7.12.2. China
    • 7.12.3. India
    • 7.12.4. South Korea
    • 7.12.5. Indonesia
    • 7.12.6. Taiwan
    • 7.12.7. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 8.1. Major Players and Strategy Analysis
  • 8.2. Emerging Players and Market Lucrativeness
  • 8.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 8.4. Vendor Competitiveness Matrix

9. COMPANY PROFILES

  • 9.1. AIDOC MEDICAL LTD.
  • 9.2. ENLITIC, INC.
  • 9.3. NUANCE COMMUNICATIONS, INC.
  • 9.4. SIEMENS HEALTHINEERS AG
  • 9.5. GE HEALTHCARE (A DIVISION OF GENERAL ELECTRIC COMPANY)
  • 9.6. ZEBRA MEDICAL VISION LTD.
  • 9.7. AGFA-GEVAERT GROUP
  • 9.8. IBM WATSON HEALTH (A DIVISION OF IBM CORPORATION)
  • 9.9. MCKESSON CORPORATION
  • 9.10. CUREMETRIX, INC.