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세계의 진단 분야 딥러닝 시장 보고서(2025년)
Deep Learning In Diagnostics Global Market Report 2025
상품코드 : 1855847
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 250 Pages
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한글목차

세계의 진단 분야 딥러닝 시장 규모는 최근 급격히 확대되고 있습니다. 2024년 25억 6,000만 달러에서 2025년에는 34억 9,000만 달러에 달하고, CAGR 36.1%로 확대될 것으로 보입니다. 역사적인 기간의 성장은 전자 의료 기록의 건강 관리 데이터 가용성 증가, 클라우드 기반 진단 플랫폼 채택 증가, 진단 소요 시간 단축에 대한 수요 증가, 개발 도상 지역의 비용 효율적인 진단 솔루션의 필요성 증가, 유전체 및 정밀 진단에서 딥러닝 사용의 확대가 이어집니다.

진단학의 딥러닝 시장 규모는 향후 수년간 비약적인 성장이 예상됩니다. 2029년까지 CAGR 35.8%로 확대되어 118억 5,000만 달러로 성장할 것으로 보입니다. 예측 기간의 성장은 조기 및 정확한 질병 검출에 대한 수요 증가, 만성 질환 및 생활 습관병 유병률 증가, AI 건강 관리 연구 개발 투자 증가, 진단 실수 감소 및 정확성 향상에 대한 필요성 증가, 디지털 병리학 및 방사선학 솔루션의 활용 확대로 이어질 것으로 예측됩니다. 예측 기간 동안 예상되는 주요 동향에는 AI를 활용한 3D 영상 진단의 진전, AI와 전자 의료 기록의 통합, 질병 검출을 위한 예측 분석의 진전, AI와 유전체 및 멀티오믹스 데이터의 통합, 자동 영상 해석의 혁신 등이 포함됩니다.

헬스케어의 디지털화 동향 증가가 진단 분야 딥러닝 시장의 확대를 촉진할 것으로 예측됩니다. 헬스케어의 디지털화는 효율성, 데이터 관리, 접근성 및 환자 관리를 개선하기 위해 의료 시스템에 디지털 기술을 통합하는 것을 의미합니다. 이러한 변화는 증가하는 환자 데이터를 관리하고 안전하게 교환할 필요성에 의해 촉진되며, 더 나은 협력과 더 많은 정보를 바탕으로 의사결정을 가능하게 합니다. 헬스케어의 디지털화는 의료 영상, 전자 의료 기록, 연결 장치 등의 소스로부터 엄청난 양의 데이터를 생성하여 진단 분야 딥러닝에 대한 수요를 낳고 있습니다. 딥러닝 기술은 이 데이터를 효율적으로 처리하고 기존 방법보다 빠르고 정확한 통찰력을 제공할 수 있습니다. 예를 들어 영국의 보건사회의료부는 2022년 6월에 2025년 3월까지 모든 NHS 트러스트가 전자 의료 기록을 도입할 전망이며, 2023년 12월까지 90%가 도입될 전망이라고 보고했습니다. 이러한 헬스케어의 디지털화 진전은 진단 분야 딥러닝 수요를 촉진하고 있습니다.

진단 분야 딥러닝 시장의 각 회사는 진단의 정확성, 속도 및 개별화된 케어를 향상시키기 위해 AI를 활용한 솔루션을 추진하고 있습니다. AI 주도 딥러닝 솔루션은 인공지능과 계층화된 신경망을 활용하여 복잡한 의료 데이터를 자동으로 분석하고, 패턴을 파악하고, 최소한의 인간 참여로 고정밀 진단 통찰력을 제공합니다. 예를 들어, 2025년 5월, 미국 의료 기술 기업인 GE Healthcare Technology는 영상 재구성과 진단 정확도 향상을 위한 CleaRecon DL을 발표했습니다. 이 시스템은 스트리크 아티팩트를 제거하여 콘빔 CT(CBCT) 이미지를 개선하고 인터벤션 치료에 보다 선명하고 정확한 이미지를 제공합니다. 임상 연구에 의하면, 이 기술에 의해 영상이 98% 선명하게 되어, 임상의의 신뢰성이 94% 향상했습니다. 이 솔루션은 워크플로우를 간소화하고 보다 효과적인 영상 유도 치료를 가능하게 함으로써 궁극적으로 환자 결과를 개선합니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 시장 : 금리, 인플레이션, 지정학, 무역전쟁과 관세, 그리고 코로나 및 회복이 시장에 미치는 영향을 포함한 거시경제 시나리오

제5장 세계의 성장 분석과 전략 분석 프레임워크

제6장 시장 세분화

제7장 지역별/국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도와 기업 프로파일

제31장 기타 주요 기업 및 혁신 기업

제32장 세계 시장 경쟁 벤치마킹과 대시보드

제33장 주요 인수합병(M&A)

제34장 최근 시장 동향

제35장 시장의 잠재력이 높은 국가, 부문, 전략

제36장 부록

JHS
영문 목차

영문목차

Deep learning in diagnostics refers to the application of advanced artificial intelligence techniques, particularly multi-layered neural networks, to analyze complex medical data such as images, signals, or patient records. It assists in identifying patterns, detecting diseases, predicting outcomes, and supporting clinical decision-making with higher speed and accuracy compared to traditional methods.

The primary components of deep learning in diagnostics include software, hardware, and services. Software consists of programs, instructions, or data that direct a computer or device to perform specific tasks. Deployment methods include cloud-based and on-premises solutions. Applications span medical imaging, pathology, genomics, drug discovery, and other areas, serving end users such as hospitals, diagnostic laboratories, research institutes, and others.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sudden escalation of U.S. tariffs and the consequent trade frictions in spring 2025 are severely impacting the healthcare sector, particularly in the supply of critical medical devices, diagnostic equipment, and pharmaceuticals. Hospitals and healthcare providers are facing higher costs for imported surgical instruments, imaging equipment, and consumables such as syringes and catheters, many of which have limited domestic alternatives. These increased costs are straining healthcare budgets, leading some providers to delay equipment upgrades or pass on expenses to patients. Additionally, tariffs on raw materials and components are disrupting the production of essential drugs and devices, causing supply chain bottlenecks. In response, the industry is diversifying sourcing strategies, boosting local manufacturing where possible, and advocating for tariff exemptions on life-saving medical products.

The deep learning in diagnostic market research report is one of a series of new reports from The Business Research Company that provides deep learning in diagnostic market statistics, including deep learning in the diagnostic industry's global market size, regional shares, competitors with deep learning in diagnostic market share, detailed deep learning in diagnostic market segments, market trends and opportunities, and any further data you may need to thrive in the deep learning in the diagnostic industry. This deep learning in diagnostic market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The deep learning in diagnostics market size has grown exponentially in recent years. It will grow from $2.56 billion in 2024 to $3.49 billion in 2025 at a compound annual growth rate (CAGR) of 36.1%. Growth in the historic period was driven by increasing availability of healthcare data from electronic health records, rising adoption of cloud-based diagnostic platforms, higher demand for faster diagnostic turnaround times, growing need for cost-effective diagnostic solutions in developing regions, and expanded use of deep learning in genomics and precision diagnostics.

The deep learning in diagnostics market size is expected to see exponential growth in the next few years. It will grow to $11.85 billion in 2029 at a compound annual growth rate (CAGR) of 35.8%. Growth in the forecast period is expected to result from rising demand for early and accurate disease detection, growing prevalence of chronic and lifestyle-related diseases, increased investment in AI healthcare research and development, stronger need to reduce diagnostic errors and improve accuracy, and greater use of digital pathology and radiology solutions. Primary trends anticipated for the forecast period include advancements in AI-powered 3D imaging, integration of AI with electronic health records, progress in predictive analytics for disease detection, incorporation of AI with genomics and multi-omics data, and innovations in automated image interpretation.

The growing trend of healthcare digitization is expected to drive the expansion of the deep learning in diagnostics market. Healthcare digitization refers to the integration of digital technologies in healthcare systems to improve efficiency, data management, accessibility, and patient care. This shift is fueled by the need to manage and securely exchange the increasing volumes of patient data, enabling better coordination and more informed decision-making. The digitization of healthcare generates vast amounts of data from sources such as medical imaging, electronic health records, and connected devices, creating a demand for deep learning in diagnostics. Deep learning technologies can process this data efficiently and deliver faster, more accurate insights than traditional methods. For example, the Department of Health and Social Care in the UK reported in June 2022 that by March 2025, all NHS trusts are expected to have implemented electronic health records, up from 90% adoption by December 2023. This rise in healthcare digitization is driving the demand for deep learning in diagnostics.

Companies in the deep learning diagnostics market are advancing AI-powered solutions to improve diagnostic accuracy, speed, and personalized care. An AI-driven deep learning solution leverages artificial intelligence and layered neural networks to automatically analyze complex medical data, identify patterns, and produce highly accurate diagnostic insights with minimal human involvement. For instance, in May 2025, GE Healthcare Technologies, a U.S.-based medical technology company, launched CleaRecon DL, designed to enhance image reconstruction and diagnostic accuracy. This system improves cone-beam CT (CBCT) images by removing streak artifacts, providing clearer and more accurate images for interventional procedures. Clinical studies have shown that the technology results in 98% clearer images and 94% improved confidence among clinicians. This solution ultimately improves patient outcomes by streamlining workflow and enabling more effective, image-guided treatments.

In November 2022, Anumana Inc., a U.S.-based AI health technology company, acquired NeuTrace Inc. for an undisclosed sum. This acquisition allows Anumana to strengthen its position in AI medical software for cardiac electrophysiology by integrating NeuTrace's EP Data Biome platform and AI-enabled electrophysiology applications into its offerings. NeuTrace specializes in AI-powered diagnostic solutions, with deep learning being a core technology for analyzing medical data such as images and signals. This partnership is expected to enhance real-time data integration and clinical decision support in the cardiac electrophysiology field.

Major players in the deep learning in diagnostics market are International Business Machines Corporation, Siemens Healthineers AG, Koninklijke Philips N.V., GE HealthCare Technologies Inc., Tempus AI Inc., Qure.ai Technologies Pvt. Ltd., Freenome Holdings Inc., PathAI Inc., Aidoc Medical Ltd., Viz.ai Inc., SOPHiA GENETICS SA, Lunit Inc., Paige.AI Inc., Beijing Infervision Technology Co. Ltd., Indica Labs Inc., CureMetrix Inc., Deep Bio Inc., Enlitic Inc., ScreenPoint Medical B.V., VUNO Inc., Mindpeak GmbH, and Arterys Inc.

North America was the largest region in the deep learning in diagnostics market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in deep learning in diagnostics report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the deep learning in diagnostics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The deep learning in diagnostics market includes revenues earned by entities by providing services such as customized algorithm development services, real-time diagnostic monitoring services, genomic and biomarker analysis services, patient data integration and interpretation services, and disease risk prediction services. The market value includes the value of related goods sold by the service provider or included within the service offering. The deep learning in diagnostics market also consists of sales of graphics processing units, edge AI devices, AI-enhanced CT scanners, and ultrasound devices. Values in this market are 'factory gate' values; that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Deep Learning In Diagnostics Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on deep learning in diagnostics market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for deep learning in diagnostics ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The deep learning in diagnostics market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

Scope

Table of Contents

1. Executive Summary

2. Deep Learning In Diagnostics Market Characteristics

3. Deep Learning In Diagnostics Market Trends And Strategies

4. Deep Learning In Diagnostics Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

5. Global Deep Learning In Diagnostics Growth Analysis And Strategic Analysis Framework

6. Deep Learning In Diagnostics Market Segmentation

7. Deep Learning In Diagnostics Market Regional And Country Analysis

8. Asia-Pacific Deep Learning In Diagnostics Market

9. China Deep Learning In Diagnostics Market

10. India Deep Learning In Diagnostics Market

11. Japan Deep Learning In Diagnostics Market

12. Australia Deep Learning In Diagnostics Market

13. Indonesia Deep Learning In Diagnostics Market

14. South Korea Deep Learning In Diagnostics Market

15. Western Europe Deep Learning In Diagnostics Market

16. UK Deep Learning In Diagnostics Market

17. Germany Deep Learning In Diagnostics Market

18. France Deep Learning In Diagnostics Market

19. Italy Deep Learning In Diagnostics Market

20. Spain Deep Learning In Diagnostics Market

21. Eastern Europe Deep Learning In Diagnostics Market

22. Russia Deep Learning In Diagnostics Market

23. North America Deep Learning In Diagnostics Market

24. USA Deep Learning In Diagnostics Market

25. Canada Deep Learning In Diagnostics Market

26. South America Deep Learning In Diagnostics Market

27. Brazil Deep Learning In Diagnostics Market

28. Middle East Deep Learning In Diagnostics Market

29. Africa Deep Learning In Diagnostics Market

30. Deep Learning In Diagnostics Market Competitive Landscape And Company Profiles

31. Deep Learning In Diagnostics Market Other Major And Innovative Companies

32. Global Deep Learning In Diagnostics Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Deep Learning In Diagnostics Market

34. Recent Developments In The Deep Learning In Diagnostics Market

35. Deep Learning In Diagnostics Market High Potential Countries, Segments and Strategies

36. Appendix

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