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시장보고서
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병리학 분야 인공지능(AI) 시장 : 시장 인사이트, 경쟁 구도 및 시장 예측(2034년)Artificial Intelligence (AI) in Pathology - Market Insights, Competitive Landscape, and Market Forecast - 2034 |
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DelveInsight
병리학 분야 인공지능(AI) 시장 요약
병리학 분야 인공지능(AI)이란, 머신러닝, 딥러닝 및 컴퓨터 비전을 디지털화된 조직 및 세포학 검체에 적용하여 질환의 감지, 등급 분류, 정량화 및 해석을 지원하는 것을 의미합니다. 전체 슬라이드 이미징 스캐너나 영상 관리 시스템과 같은 디지털 병리의 기반을 바탕으로, AI 알고리즘은 고해상도 슬라이드 이미지를 분석하여 의심스러운 병변을 식별하고, 면역조직화학 및 바이오마커 점수를 산출하며, 종양 특성의 정량화, 동반 진단 지원을 수행하며, 사례 분류, 품질 관리, 디지털 보고서 작성을 통해 워크플로우를 최적화합니다. 이 시장은 알고리즘 및 이미지 관리 플랫폼과 같은 소프트웨어와 스캐너 및 컴퓨팅 인프라와 같은 하드웨어, 나아가 도입, 통합, 관리형 분석에 이르는 서비스를 결합한 것입니다. 핵심 기술로는 컨볼루션 신경망 및 기타 신경망, 컴퓨터 비전, 그리고 수백만 장의 슬라이드로 학습된 신흥 생성 모델 및 기반 모델이 포함됩니다. 그 용도 분야는 종양학 및 비종양성 질환의 해부병리학, 동반 진단, 원격 병리학, 바이오마커 주도 정밀의료, 제약 연구에 이릅니다. FDA 승인, EU의 IVDR 인증, 대규모 기반 모델의 도입 및 업계 재편 움직임과 같은 일련의 동향에 힘입어, AI는 현대 병리학에서 가장 혁신적인 원동력이 되어 이 분야를 유리 슬라이드 중심에서 컴퓨터를 활용한 데이터 주도형 진단으로 전환시키고 있습니다.
병리학 분야 AI 시장의 주요 시장 성장 촉진요인
병리학 분야 인공지능(AI) 시장 성장에 기여하는 요인
시장 성장 촉진요인
세계 암 부담 증가 및 슬라이드 수 증가
병리학 분야 인공지능(AI) 시장의 가장 강력한 촉진요인은 세계 암 부담 증가입니다. 이로 인해 생검 및 슬라이드 처리량이 증가하고, 진단의 복잡성도 높아지고 있습니다. 국제암연구소(IARC)의 기록에 따르면, 2022년 신규 암 환자 수는 2,000만 명이었으나, 2050년까지 3,500만 명에 달할 것으로 예측됩니다. 또한 전립선암 등 일반적인 악성 종양의 발생률은 급격히 상승할 것으로 보이며, 세계 전립선암 환자 수는 2040년까지 2배로 늘어날 것으로 예측됩니다. 암 검사를 할 때마다 조직 표본이나 세포진 슬라이드가 생성되며, 이들은 검사, 악성도 분류, 특성 분석을 거쳐야 합니다. 더 나아가 정밀 종양학 및 동반 진단 워크플로우에서는 바이오마커 및 면역조직화학 점수 산출도 추가됩니다. 병리학 분야 인공지능(AI)은 의심스러운 병변의 감지, 종양의 악성도 분류, 바이오마커의 정량화를 신속하고 일관되게 수행함으로써 이러한 증가하는 업무 부하에 직접 대응하고 있습니다. 암 발병률이 상승하고 진단의 복잡성이 증가함에 따라, 병리 전문의의 업무를 지원하는 AI에 대한 수요가 높아져 2034년까지 시장 성장을 뒷받침할 것입니다.
병리 전문의 부족 심화와 사례 수 증가
세계적인 병리 전문의 부족 심화와 사례 수 증가가 맞물려 AI 도입의 주요 촉진요인이 되고 있습니다. 훈련을 받은 병리 전문의 공급은 수요에 비해 훨씬 더 느린 속도로만 증가하고 있으며, 그 결과 검사 지연, 소견 보고까지의 기간 장기화, 번아웃, 그리고 소견의 편차가 발생하고 있습니다. 특히 주요 학술 기관 이외의 곳이나 자원이 부족한 지역에서는 그 부족 현상이 극히 심각합니다. 병리 분야의 AI는 반복적인 검출 및 측정 작업의 자동화, 사례 분류, 정량 분석 초안 작성, 그리고 병리 전문의가 간과하기 쉬운 미세 암이나 희귀 암을 지적하는 진단상의 안전망 역할을 수행함으로써 이러한 격차를 완화합니다. 인력을 비례적으로 늘리지 않고도 처리 능력, 일관성, 접근성을 향상시킴으로써 AI는 가장 많은 사례를 다루는 병원 및 검사 기관에 명확한 업무적 가치를 제공합니다. 이러한 구조적인 인력 부족의 압박은 예측 기간 동안 임상 현장 및 검사 기관 전반에 걸쳐 AI를 통한 업무 지원에 대한 수요를 촉진할 것입니다.
시장 제약 요인
성장세는 강하지만, 병리학 분야 인공지능(AI) 시장은 중대한 제약에 직면해 있습니다. 디지털화 및 AI를 활용한 병리학으로의 전환에는 전체 슬라이드 이미징 스캐너, 스토리지 및 컴퓨팅 인프라, 검사 시스템과의 통합이 필요하며, 이는 소규모이고 자원이 제한된 검사실에게 큰 비용 부담이 되므로 막대한 자본 요건이 큰 장벽이 되고 있습니다. 규제 및 임상 검증 요건도 복잡성을 더하고 있습니다. AI 진단 도구는 명확한 임상적 유효성을 입증하고, 지속적으로 진화하는 FDA 및 EU의 IVDR(체외진단의료기기규정) 프레임워크를 준수해야 하기 때문에 개발 기간이 길어지고, 시판 후 지속적인 성능 모니터링이 필요합니다. AI 시스템의 개발, 검증, 운영이 가능한 숙련된 전문가의 부족이 도입을 제약하고 있으며, 조사에 따르면 대부분의 조직이 유능한 AI 인재 확보에 어려움을 겪고 있는 것으로 나타났습니다. 스캐너, 이미지 형식, AI 플랫폼 간의 상호 운용성 및 표준화 격차는 통합과 재현성을 복잡하게 만들고 있으며, 독자적인 형식이 여전히 존재하고 있다는 점이 확장성을 저해하고 있습니다. 알고리즘의 편향성, 다양한 집단에서의 범용성, AI가 관여한 진단에 대한 설명 책임에 대한 우려로 인해 투명성과 견고한 검증이 요구되고 있으므로, 임상의의 신뢰는 여전히 장벽으로 남아 있습니다. AI를 활용한 병리 진단에 대한 보험 급여는 지역에 따라 여전히 불균일하고 미성숙한 상태이며, 이는 투자 수익률을 제약하고 있습니다. 한편, 대규모 슬라이드 데이터셋과 관련된 데이터 개인정보 보호, 거버넌스, 사이버 보안 의무도 부담으로 작용하고 있습니다. 이러한 자본, 규제, 인재, 상호운용성, 신뢰, 보험 환급과 같은 장벽들이 복합적으로 작용하여, 암의 부담, 인력 부족, 디지털화와 같은 근본적인 촉진요인이 여전히 견조함에도 불구하고 성장 속도를 둔화시키고 있습니다.
경쟁 구도는 다음과 같은 측면에서 평가할 수 있습니다.
병리학 분야 AI 시장 보고서 조사에서 도출된 주요 포인트
본 ‘병리학 분야 인공지능(AI) 시장’ 보고서 조사를 통해 혜택을 얻을 수 있는 대상 독자
병리학 분야 인공지능(AI) 시장 및 해당 시장의 최신 기술 동향에 대해 자세히 알고자 하는 다양한 최종 사용자.
Q1. 병리학 분야 인공지능(AI) 시장 성장률은 어느 정도입니까?
병리학 분야 인공지능(AI) 시장은 2026-2034년 예측 기간 동안 연평균 성장률(CAGR) 24.7%로 확대될 것으로 전망됩니다.
Q2. 병리학 분야 인공지능(AI) 시장 규모는 어느 정도입니까?
병리학 분야 인공지능(AI) 시장 규모는 2025년에 1억 3,000만 달러로 평가되었고, 2034년까지 9억 5,000만 달러에 달할 것으로 예측됩니다.
Q3. 병리학 분야 인공지능(AI) 시장을 주도하는 지역은 어디인가?
북미는 선진적인 의료 인프라, 높은 디지털 병리학 보급률, 가장 활발한 FDA 승인 및 지침 환경, 기반 모델 분야의 리더십, 그리고 AI 병리학 개발사가 밀집해 있는 기반을 바탕으로 2025년에는 세계 매출의 41%를 차지하며 AI 병리학 시장을 주도했습니다. 아시아태평양은 예측 기간 동안 가장 빠르게 성장할 지역입니다.
Q4. 병리학 분야 인공지능(AI) 시장을 주도하는 주요 요인은?
주요 촉진요인으로는 세계 암 환자 수 증가를 들 수 있습니다. 국제암연구소(IARC)의 예측에 따르면, 암 환자 수는 2022년 2,000만 명에서 2050년까지 3,500만 명으로 증가할 것으로 전망됩니다. 또한, 사례 수 증가에 따라 병리 전문의 부족이 심화되고 있는 점, 규제 당국의 승인이 가속화되어 FDA 승인 건수가 2025년에는 10건에 달할 것으로 예상되는 점, 유리 슬라이드에서 디지털 병리학으로의 전환, 그리고 파운데이션 모델 및 생성형 AI 코파일럿의 등장 등이 있습니다.
Q5. 병리학 분야 인공지능(AI) 시장을 주도하는 주요 기업은?
주요 기업으로는 Tempus AI, Inc.(Paige), F. Hoffmann-La Roche Ltd, Koninklijke Philips N.V., PathAI, Inc., Ibex Medical Analytics Ltd., Proscia Inc., Indica Labs, Inc., Aiforia Technologies Plc, Hologic, Inc., Visiopharm A/S 등이 있습니다. 이 외에도 ‘경쟁 구도’ 섹션에서 소개된 기타 활발히 개발 중인 기업들과 Akoya Biosciences, Mindpeak, ArteraAI도 주요 업체에 포함됩니다. Tempus(Paige), Roche, Philips, PathAI 및 Ibex는 검증된 플랫폼과 규제 당국의 승인을 통해 업계를 선도하고 있습니다.
AI in Pathology Market Summary
Artificial intelligence (AI) in pathology refers to the application of machine learning, deep learning, and computer vision to digitized tissue and cytology specimens to assist in the detection, grading, quantification, and interpretation of disease. Building on the digital-pathology foundation of whole-slide imaging scanners and image management systems, AI algorithms analyze high-resolution slide images to flag suspicious foci, score immunohistochemistry and biomarkers, quantify tumor features, support companion diagnostics, and optimize workflow through case triage, quality control, and digital reporting. The market combines software, including algorithms and image-management platforms, with hardware such as scanners and computing infrastructure, and services spanning deployment, integration, and managed analytics. Core technologies include convolutional and other neural networks, computer vision, and emerging generative and foundation models trained on millions of slides. Applications span anatomic pathology in oncology and non-oncologic disease, companion diagnostics, telepathology, biomarker-driven precision medicine, and pharmaceutical research. Accelerated by a wave of FDA authorizations, EU IVDR certifications, and large foundation-model and consolidation moves, AI has become the most transformative force in modern pathology, shifting the field from glass slides toward computational, data-driven diagnosis.
AI in Pathology Market Key Growth Drivers
Key Companies in AI in Pathology Market
The competitive landscape is led by the following active developers and providers:
Factors Contributing to the Growth of the AI in Pathology Market
Market Drivers
Rising Global Cancer Burden and Slide Volumes
The most powerful driver of the AI in Pathology market is the rising global cancer burden, which increases biopsy and slide volumes and the complexity of diagnosis. The International Agency for Research on Cancer recorded 20 million new cancer cases in 2022 and projects 35 million by 2050, and the incidence of common malignancies such as prostate cancer is expected to rise sharply, with global prostate cancer cases projected to double by 2040. Each cancer workup generates tissue and cytology slides that must be examined, graded, and characterized, and precision-oncology and companion-diagnostic workflows add biomarker and immunohistochemistry scoring. AI in pathology directly addresses this growing workload by detecting suspicious foci, grading tumors, and quantifying biomarkers with speed and consistency. As cancer incidence climbs and diagnostic complexity deepens, demand for AI that augments pathologists expands, anchoring market growth through 2034.
Worsening Shortage of Pathologists and Rising Caseloads
A worsening global shortage of pathologists, combined with rising caseloads, is a central driver of AI adoption. The supply of trained pathologists is growing far more slowly than demand, producing backlogs, longer turnaround times, burnout, and variability in interpretation, with shortages especially acute outside major academic centers and in lower-resource regions. AI in pathology mitigates this gap by automating repetitive detection and measurement tasks, triaging cases, generating draft quantification, and acting as a diagnostic safety net that flags small or rare cancers a pathologist might miss. By improving throughput, consistency, and access without proportionally increasing staffing, AI delivers clear operational value to hospitals and reference laboratories handling the largest case volumes. This structural workforce pressure reinforces demand for AI augmentation across clinical and reference settings throughout the forecast period.
Market Restraints
Despite strong momentum, the AI in Pathology market faces material constraints. High capital requirements are a significant barrier, as the transition to digital and AI-enabled pathology demands whole-slide imaging scanners, storage and computing infrastructure, and integration with laboratory systems, costs that are difficult for smaller and lower-resource laboratories to absorb. Regulatory and clinical-validation requirements add complexity, as AI diagnostic tools must demonstrate clear clinical benefit and navigate evolving FDA and EU IVDR frameworks, lengthening development timelines and requiring ongoing post-market performance monitoring. A shortage of skilled professionals able to develop, validate, and operate AI systems constrains deployment, with surveys indicating most organizations struggle to find qualified AI talent. Interoperability and standardization gaps between scanners, image formats, and AI platforms complicate integration and reproducibility, and the persistence of proprietary formats slows scalability. Clinician trust remains a gating factor, as concerns about algorithmic bias, generalizability across diverse populations, and accountability for AI-influenced diagnoses require transparency and robust validation. Reimbursement for AI-enabled pathology remains uneven and immature across geographies, constraining return on investment, while data-privacy, governance, and cybersecurity obligations involving large slide datasets add burden. Together, these capital, regulatory, workforce, interoperability, trust, and reimbursement barriers temper the pace of growth, even as the underlying drivers of cancer burden, workforce shortage, and digitization remain firmly intact.
AI in Pathology Market Segment Analysis
The AI in Pathology Market by Offering (Software, Hardware, Services), Technology (Machine Learning, Deep Learning, Computer Vision, Generative and Foundation Models, Others), Application (Disease Diagnosis and Prognosis, Drug Discovery and Development, Companion Diagnostics, Workflow and Quality Control, Others), End User (Hospitals and Reference Laboratories, Diagnostic Laboratories, Pharmaceutical and Biotechnology Companies, Research and Academic Institutes, Others), and Geography (North America, Europe, Asia-Pacific, Rest of World).
By Offering
Dominant Subsegment: Software. The software category is expected to dominate the market.
Dominant: Software ~ 51%
The software segment accounted for 51% of the AI in Pathology market in 2025. Software is the leading offering because the value of AI in pathology resides in the algorithms and image-management platforms that detect cancer, grade tumors, quantify biomarkers, and orchestrate workflow, and because software generates recurring revenue through licenses, subscriptions, and cloud services. Cloud-native image management systems that unify slide viewing, collaboration, and integrated AI, such as enterprise platforms deployed across hospital networks, anchor the segment, while clinically validated algorithms address detection, grading, and biomarker scoring. FDA-cleared software and image-management stacks are normalizing multi-AI workflows, allowing laboratories to add modules over time and expanding software spend across the installed base. The shift toward foundation models trained on millions of slides deepens the software tier further by enabling broad, generalizable capabilities. Because algorithms improve continuously and scale without proportional hardware, software commands the largest and most durable share, while hardware such as scanners provides the imaging substrate and services support deployment, integration, and managed analytics.
By Technology
Dominant Subsegment: Machine Learning. The machine learning category is expected to dominate the market.
Dominant: Machine Learning ~ 45%
The machine learning segment accounted for 45% of the AI in Pathology market in 2025. Machine learning is the leading technology because it underpins the majority of deployed AI pathology applications, with convolutional and other neural networks trained on annotated whole-slide images powering cancer detection, grading, and biomarker quantification. Trained on large labeled datasets, machine-learning models deliver the pattern-recognition capabilities that pathologists rely on, and they form the foundation on which deep learning, a specialized subset, extends performance for complex histopathology. The segment's dominance reflects maturity, regulatory familiarity, and broad integration across cleared clinical tools from Tempus' Paige, Ibex, and others. Adjacent technologies are advancing quickly: computer vision powers image analysis and is among the fastest-growing approaches, while generative and foundation models trained on millions of slides are expanding rapidly for biomarker discovery and diagnostic co-pilots. While these newer approaches grow fast from smaller bases, machine learning retains leadership in 2025 through its breadth of validated, deployed clinical applications across the installed base.
By End User
Dominant Subsegment: Hospitals and Reference Laboratories. The hospitals and reference laboratories category is expected to dominate the market.
Dominant: Hospitals and Reference Laboratories ~ 47%
The hospitals and reference laboratories segment accounted for 47% of the AI in Pathology market in 2025. Hospitals and reference laboratories are the largest end user because they process the highest volume of pathology cases and have the scale, infrastructure, and clinical breadth to adopt digital pathology and enterprise AI platforms. These facilities anchor the installed base for whole-slide imaging and image-management systems, and they deploy AI to accelerate detection, standardize grading, and manage rising caseloads amid pathologist shortages. Large hospital networks and national laboratories are implementing enterprise platforms that unify slide management with integrated AI across many sites, exemplified by health systems and nationwide pathology networks adopting cloud-native image-management systems. This concentration of volume and infrastructure drives the bulk of AI pathology demand. At the same time, pharmaceutical and biotechnology companies and research and academic institutes are growing quickly as biomarker discovery and clinical-trial applications expand. Nonetheless, the volume, infrastructure, and clinical centrality of hospitals and reference laboratories secure their leadership across the forecast period.
AI in Pathology Market Region Analysis
Dominant Region: North America
North America accounted for 41% of the global AI in Pathology market revenue in 2025, representing the highest regional market share globally. The region's dominance reflects advanced healthcare infrastructure, high adoption of digital pathology, substantial AI investment, and the most active regulatory environment, particularly in the United States. North America hosts the largest concentration of AI pathology developers, including Tempus, Paige, PathAI, and Proscia, and benefits from a steady cadence of FDA authorizations, with AI pathology clearances rising to ten in 2025 and the FDA issuing clarifying guidance on AI-enabled devices. The region leads in foundation-model development, exemplified by the Tempus acquisition of Paige to build a large oncology foundation model, and in enterprise deployments across hospital and reference-laboratory networks. Strong precision-oncology and companion-diagnostic programs, deep venture and strategic investment, and integration with electronic health records reinforce adoption. A dense developer base, regulatory clarity, and digitized infrastructure anchor the region's continued leadership.
Dominant: North America ~ 41% (Largest)
Fastest Growing Region: Asia-Pacific
Asia-Pacific is the fastest-growing region in the AI in Pathology market. The region's elevated CAGR is driven by a large and rising cancer burden, an acute shortage of pathologists relative to population, expanding healthcare investment, and rapid digitization across China, Japan, India, South Korea, and Australia. Severe pathologist shortages in populous markets make AI augmentation and telepathology especially valuable for extending diagnostic capacity, and active regional developers in China, Korea, and Taiwan are scaling computational pathology platforms. Government digital-health initiatives, growing precision-oncology adoption, and increasing laboratory digitization are accelerating deployment, while lower-cost local solutions broaden access. The combination of high disease burden, workforce constraints, and rapid digitization positions Asia-Pacific as the principal source of incremental growth over the forecast period.
Regional Commentary
North America
North America accounted for 41% of the global AI in Pathology market revenue in 2025. The United States dominates on the strength of its developer base, high digital-pathology adoption, the most active FDA authorization and guidance environment, leadership in foundation models, and integration with precision-oncology and companion-diagnostic programs, while Canada contributes through hospital and academic adoption.
Europe
Europe is a large and advanced regional market, led by Germany, the United Kingdom, France, Italy, and Spain. Growth is supported by strong public health systems, regional digital-pathology initiatives, and the EU In Vitro Diagnostic Regulation, which raises the evidence bar and, through IVDR certification of leading AI tools, validates clinical performance. A strong base of European developers, including Aiforia, Visiopharm, Mindpeak, and Tribun Health, reinforces the region's position.
Asia-Pacific
Asia-Pacific is the fastest-growing region, propelled by a rising cancer burden, acute pathologist shortages, expanding healthcare investment, and rapid digitization across China, Japan, India, South Korea, and Australia. Regional developers in China, Korea, and Taiwan scale computational pathology platforms, while government digital-health programs and telepathology extend diagnostic access across large and underserved populations.
Rest of World
The Rest of World region, spanning Latin America, the Middle East, and Africa, is an emerging growth frontier. A rising cancer burden, severe shortages of pathologists, and limited laboratory capacity make AI augmentation and telepathology especially valuable, and government digitization initiatives and partnerships, such as large integrated healthcare networks adopting AI image-management systems, are expanding access across these markets.
AI in Pathology Market Competitive Landscape
The AI in Pathology market is classified as Moderately Concentrated. A group of leading AI pathology developers and diagnostics majors, including Tempus with Paige, Roche, Philips, PathAI, and Ibex, holds substantial share through advanced platforms, clinical collaborations, and regulatory clearances, while a dynamic field of specialized providers such as Proscia, Indica Labs, Aiforia, Visiopharm, Hologic, and Mindpeak competes across image management, biomarker analysis, and specific cancer indications, increasing competition in fast-growing segments.
The competitive landscape can be evaluated across the following dimensions:
AI in Pathology Market Recent Developmental Activities
In August 2025, Tempus AI, Inc. completed the acquisition of Paige, merging Paige's 7 million digitized slides with Tempus' multiomic data with the stated goal of building the largest foundation model in oncology. Strategic significance: Creates a leading data and foundation-model position and accelerates the path from discovery to regulated AI pathology tools.
In August 2025, PathAI, Inc. (with Moffitt Cancer Center) announced a multi-year strategic partnership to implement the AISight Dx cloud-native digital pathology platform across Moffitt's pathology operations. Strategic significance: Anchors enterprise-scale AI pathology adoption at a leading cancer center and showcases unified slide management with integrated AI.
AI in Pathology Market Segmentation
AI in Pathology Market by Offering
AI in Pathology Market by Technology
AI in Pathology Market by Application
AI in Pathology Market by End User
AI in Pathology Market by Geography
Key Takeaways from the AI in Pathology Market Report Study
Target audience who can benefit from this AI in pathology market report study
Various end-users who want to know more about the AI in pathology market and the latest technological developments in the AI in pathology market.
Q1. What is the growth rate of the AI in Pathology market?
The AI in Pathology market is projected to expand at a CAGR of 24.7% during the forecast period from 2026-2034.
Q2. What is the market size of the AI in Pathology market?
The AI in Pathology market is estimated at USD 0.13 billion in 2025 and is projected to reach USD 0.95 billion by 2034.
Q3. Which region dominates the AI in Pathology market?
North America dominated the AI in Pathology market with a 41% share of global revenue in 2025, supported by advanced healthcare infrastructure, high digital-pathology adoption, the most active FDA authorization and guidance environment, leadership in foundation models, and a dense base of AI pathology developers. Asia-Pacific is the fastest-growing region over the forecast period.
Q4. What are the key drivers of the AI in Pathology market?
The principal drivers are the rising global cancer burden, with the International Agency for Research on Cancer projecting cancer cases to rise from 20 million in 2022 to 35 million by 2050; a worsening shortage of pathologists amid rising caseloads; accelerating regulatory clearances, with FDA authorizations rising to ten in 2025; the transition from glass slides to digital pathology; and the emergence of foundation models and generative AI co-pilots.
Q5. Who are the major players in the AI in Pathology market?
The major players include Tempus AI, Inc. (Paige), F. Hoffmann-La Roche Ltd, Koninklijke Philips N.V., PathAI, Inc., Ibex Medical Analytics Ltd., Proscia Inc., Indica Labs, Inc., Aiforia Technologies Plc, Hologic, Inc., and Visiopharm A/S, among other active developers profiled in the Competitive Landscape section, along with Akoya Biosciences, Mindpeak, and ArteraAI. Tempus with Paige, Roche, Philips, PathAI, and Ibex lead through validated platforms and regulatory clearances.
For illustrative purposes, only the top 10 companies are listed in the Table of Contents. The report may include analysis and references to additional companies where relevant to the market assessment.