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市場調查報告書
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1574170

放射學工作流程最佳化中的人工智慧 (AI) 市場:2024 年至 2029 年預測

Artificial Intelligence (AI) in Radiology Workflow Optimization Market - Forecasts from 2024 to 2029

出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 131 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

放射學工作流程最佳化中的人工智慧(AI)市場預計將以32.56%的複合年成長率成長,2029年市場規模為4,932,358,000美元,預計2024年將達到1,204,935,000美元。

人工智慧正在徹底改變放射學工作流程增強領域,開創準確性和效率的新時代。隨著對能夠提供快速、準確診斷的解決方案的需求不斷成長,人工智慧驅動的解決方案已成為一個轉折點和遊戲規則改變者。人工智慧整合解決方案透過為放射科醫生提供足夠的資訊、減少誤診並加速患者疾病的早期診斷,促進適當的醫學影像解讀。

因此,人工智慧透過減少影像因果關係和影像分類等日常任務來最佳化輸出,使放射科醫生能夠更專注於複雜和具有挑戰性的病例。放射學工作流程最佳化中的人工智慧市場目前正處於積極成長階段,因為領先的醫療保健提供者和診斷成像中心可以輕鬆採用這些解決方案。將人工智慧納入放射學業務預計將透過改善患者治療結果、降低成本和簡化流程來改變醫療保健服務。

放射學工作流程最佳化中的人工智慧 (AI) 市場促進因素:

  • 由於重複性任務的自動化,預計市場將成長

放射學工作流程最佳化中的人工智慧 (AI) 市場對於提高放射學實踐效率的重複流程自動化至關重要。由機器學習驅動的演算法可以快速篩選與各種醫學影像(包括 X 光和 MRI)相關的大量資料,發現相似性和不規則性。分割影像、提取特定特徵和搜尋過去類似病例等任務可以自動化,使放射科醫生能夠騰出時間來處理更複雜和重要的病例。這種簡化的過程提高了放射學的效率,從而可以更快地進行診斷並改善患者的治療結果。自動化消除了人為錯誤並創造了一致性,這對醫療保健專業人員和患者都有好處。

放射學工作流程最佳化中人工智慧 (AI) 市場的地域展望

  • 北美在預測期內將經歷指數級成長

北美已成為放射學工作流程最佳化人工智慧 (AI) 市場的市場領導者。北美的優勢源自於其強大的醫療體系、人工智慧技術的快速融合以及研發的高投入。此外,該地區也是多家推動創新的著名人工智慧和醫療技術公司的所在地。隨著該地區對精準醫療和以患者為中心的護理的關注,人工智慧驅動的放射技術正在投入大量資金,這引起了醫療保健提供者和醫療機構的極大興趣。據估計,北美將繼續在新興技術領域處於領先地位,特別是隨著其人口預計將成長並接受人工智慧。

為什麼要購買這份報告?

  • 富有洞察力的分析:獲得涵蓋關鍵和新興地區的深入市場洞察,重點關注客戶細分、政府政策和社會經濟因素、消費者偏好、行業部門和其他子區隔。
  • 競爭格局:了解世界主要參與者所採取的策略策略,並了解採用正確策略滲透市場的潛力。
  • 市場促進因素和未來趨勢:探索動態因素和關鍵市場趨勢以及它們將如何塑造未來市場開拓。
  • 可行的建議:利用洞察力做出策略決策,以在動態環境中發現新的業務流和收益。
  • 面向廣大受眾:對於新興企業、研究機構、顧問、中小型企業和大型企業有用且具有成本效益。

公司使用我們的報告的目的是什麼?

產業與市場考量、機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開拓、競爭影響

調查範圍

  • 2022年至2029年歷史資料與預測
  • 成長機會、挑戰、供應鏈前景、法規結構、客戶行為和趨勢分析
  • 競爭定位、策略和市場佔有率分析
  • 區域分析,包括收益成長以及預測細分市場和國家
  • 公司概況(尤其是關鍵發展)

放射學工作流程最佳化市場中的人工智慧(AI)細分和分析如下:

依技術

  • 機器學習
  • 深度學習
  • 自然語言處理(NLP)
  • 電腦視覺
  • 其他

按用途

  • 影像擷取與預處理
  • 影像分析與解釋
  • 報告和文件
  • 品管與保證
  • 其他

按最終用戶

  • 醫院/診所
  • 影像診斷中心
  • 研究機構/學術中心
  • 其他

按地區

  • 北美洲
  • 美國
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他
  • 歐洲
  • 英國
  • 德國
  • 法國
  • 義大利
  • 西班牙
  • 其他
  • 中東 中東/非洲
  • 沙烏地阿拉伯
  • UAE
  • 其他
  • 亞太地區
  • 日本
  • 中國
  • 印度
  • 韓國
  • 印尼
  • 台灣
  • 其他

目錄

第1章簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關利益者的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現
  • CXO觀點

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章放射學工作流程最佳化中的人工智慧 (AI) 市場:按技術分類

  • 介紹
  • 機器學習
  • 深度學習
  • 自然語言處理(NLP)
  • 電腦視覺
  • 其他

第6章放射學工作流程最佳化中的人工智慧 (AI) 市場:按應用分類

  • 介紹
  • 影像擷取與預處理
  • 影像分析與解釋
  • 報告和文件
  • 品管與保證
  • 其他

第7章放射學工作流程最佳化中的人工智慧 (AI) 市場:按最終用戶分類

  • 介紹
  • 醫院/診所
  • 影像診斷中心
  • 研究機構/學術中心
  • 其他

第8章放射學工作流程最佳化中的人工智慧(AI)市場:按地區

  • 介紹
  • 北美洲
    • 依技術
    • 按用途
    • 按最終用戶
    • 按國家/地區
  • 南美洲
    • 依技術
    • 按用途
    • 按最終用戶
    • 按國家/地區
  • 歐洲
    • 依技術
    • 按用途
    • 按最終用戶
    • 按國家/地區
  • 中東/非洲
    • 依技術
    • 按用途
    • 按最終用戶
    • 按國家/地區
  • 亞太地區
    • 依技術
    • 按用途
    • 按最終用戶
    • 按國家/地區

第9章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第10章 公司簡介

  • Aidoc Medical Ltd.
  • Zebra Medical Vision Ltd.
  • Enlitic, Inc.
  • Butterfly Network, Inc.
  • IBM Watson Health(A Division of IBM Corporation)
  • Siemens Healthineers Ag
  • Ge Healthcare(A Division of General Electric Company)
  • Nvidia Corporation
  • Imagen Technologies, Inc.
  • Koninklijke Philips NV
簡介目錄
Product Code: KSI061615947

Artificial Intelligence (AI) in the radiology workflow optimization market is expected to grow at a CAGR of 32.56%, reaching a market size of US$4,932.358 million in 2029 and US$1,204.935 million in 2024.

AI has disrupted the radiology workflow enhancement field, marking a new dawn of precision and efficiency. Due to the growing demand for solutions that can offer speedy and precise diagnosis, AI-powered solutions have been a turning point and have transformed the situation. AI-integrated solutions facilitate appropriate medical imaging interpretation by providing the radiologist with adequate information, mitigating misdiagnosis, and aiding in the speed of the early diagnosis of illness in patients.

Therefore, AI optimizes the output by reducing mundane activities such as image causation and image classification, allowing radiologists to focus more on intricate and challenging cases. The market for AI in radiology workflow optimization is currently in a forward growth phase with the ready adoption of these solutions by major healthcare providers and imaging centers. AI's incorporation into radiology operations promises to alter healthcare delivery by improving patient outcomes, lowering costs, and streamlining processes.

Artificial Intelligence (AI) in Radiology Workflow Optimization Market Drivers:

  • Automation of repetitive tasks is anticipated to increase the market growth

The automation of repetitive processes is critical in altering the efficiency of radiology practices in the AI in the radiology workflow optimization market. The machine learning-powered algorithms can quickly screen through extensive amounts of data related to different medical images, including X-rays and MRIs, to find similarities and irregularities. Tasks such as image splitting, extraction of certain properties, and searching for similar cases in history can be automated so that radiologists can work on more complex and important cases. This simplification of processes improves the efficiency of radiology and enables speedier diagnoses and enhanced patient outcomes. Automation eliminates human error and creates uniformity, which works well for both the medical professional and the patient.

Artificial Intelligence (AI) in Radiology Workflow Optimization Market Geographical Outlook

  • North America is witnessing exponential growth during the forecast period

North America has emerged as the market leader in AI in the radiology workflow optimization market. North America's preponderance can be attributed to its robust healthcare system, quick integration of AI technologies, and high investments in research and development. Furthermore, several prominent AI and health technology companies that foster innovations are found in the region. The region's focus on precision medicine and patient-centered care has led to significant funding for AI-oriented radiology technologies that greatly interest healthcare providers and institutions. It is estimated that North America will continue to lead in emerging technologies, especially due to the population's anticipated growth and acceptance of AI.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The Artificial Intelligence (AI) in radiology workflow optimization market is segmented and analyzed as follows:

By Technology

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

By Application

  • Image Acquisition And Preprocessing
  • Image Analysis And Interpretation
  • Reporting And Documentation
  • Quality Control And Assurance
  • 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
  • 1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Processes

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings
  • 3.2. CXO Perspective

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's 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
  • 4.5. Analyst View

5. ARTIFICIAL INTELLIGENCE (AI) IN RADIOLOGY WORKFLOW OPTIMIZATION MARKET BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. Machine Learning
  • 5.3. Deep Learning
  • 5.4. Natural Language Processing (NLP)
  • 5.5. Computer Vision
  • 5.6. Others

6. ARTIFICIAL INTELLIGENCE (AI) IN RADIOLOGY WORKFLOW OPTIMIZATION MARKET BY APPLICATION

  • 6.1. Introduction
  • 6.2. Image Acquisition And Preprocessing
  • 6.3. Image Analysis And Interpretation
  • 6.4. Reporting And Documentation
  • 6.5. Quality Control And Assurance
  • 6.6. Others

7. ARTIFICIAL INTELLIGENCE (AI) IN THE RADIOLOGY WORKFLOW OPTIMIZATION 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

8. ARTIFICIAL INTELLIGENCE (AI) IN RADIOLOGY WORKFLOW OPTIMIZATION MARKET BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Technology
    • 8.2.2. By Application
    • 8.2.3. By End-User
    • 8.2.4. By Country
      • 8.2.4.1. United States
      • 8.2.4.2. Canada
      • 8.2.4.3. Mexico
  • 8.3. South America
    • 8.3.1. By Technology
    • 8.3.2. By Application
    • 8.3.3. By End-User
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
      • 8.3.4.2. Argentina
      • 8.3.4.3. Others
  • 8.4. Europe
    • 8.4.1. By Technology
    • 8.4.2. By Application
    • 8.4.3. By End-User
    • 8.4.4. By Country
      • 8.4.4.1. United Kingdom
      • 8.4.4.2. Germany
      • 8.4.4.3. France
      • 8.4.4.4. Italy
      • 8.4.4.5. Spain
      • 8.4.4.6. Others
  • 8.5. Middle East and Africa
    • 8.5.1. By Technology
    • 8.5.2. By Application
    • 8.5.3. By End-User
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
      • 8.5.4.2. UAE
      • 8.5.4.3. Others
  • 8.6. Asia Pacific
    • 8.6.1. By Technology
    • 8.6.2. By Application
    • 8.6.3. By End-User
    • 8.6.4. By Country
      • 8.6.4.1. Japan
      • 8.6.4.2. China
      • 8.6.4.3. India
      • 8.6.4.4. South Korea
      • 8.6.4.5. Indonesia
      • 8.6.4.6. Taiwan
      • 8.6.4.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. Aidoc Medical Ltd.
  • 10.2. Zebra Medical Vision Ltd.
  • 10.3. Enlitic, Inc.
  • 10.4. Butterfly Network, Inc.
  • 10.5. IBM Watson Health (A Division of IBM Corporation)
  • 10.6. Siemens Healthineers Ag
  • 10.7. Ge Healthcare (A Division of General Electric Company)
  • 10.8. Nvidia Corporation
  • 10.9. Imagen Technologies, Inc.
  • 10.10. Koninklijke Philips N.V.