Digital Intelligence Pathology Platform and Its Service Pattern

Pathological diagnosis is the cornerstone for clinical diagnosis and treatment decision-making. The digital intelligence pathology platform built by integrating artificial intelligence, big data, and other information technologies has great application values, which will support the digitalization a...

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Main Authors: Xiaohong Chen, Liu Liu, Yajua Niu, Xiaoliang Liu, Xiaohai Li, Jianhua Zhou, Junpu Wang
Format: Article
Language:zho
Published: 《中国工程科学》杂志社 2025-04-01
Series:中国工程科学
Subjects:
Online Access:https://www.engineering.org.cn/sscae/EN/PDF/10.15302/J-SSCAE-2024.11.024
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author Xiaohong Chen
Liu Liu
Yajua Niu
Xiaoliang Liu
Xiaohai Li
Jianhua Zhou
Junpu Wang
author_facet Xiaohong Chen
Liu Liu
Yajua Niu
Xiaoliang Liu
Xiaohai Li
Jianhua Zhou
Junpu Wang
author_sort Xiaohong Chen
collection DOAJ
description Pathological diagnosis is the cornerstone for clinical diagnosis and treatment decision-making. The digital intelligence pathology platform built by integrating artificial intelligence, big data, and other information technologies has great application values, which will support the digitalization and intelligent upgrading of the pathology discipline and expand the Chinese solution of intelligent pathology. This study systematically clarifies the conceptual framework of digital intelligence pathology, identifies practical application requirements, and highlights critical challenges in its implementation. Building on proprietary research achievements, we propose a tripartite middleware architecture comprising data, algorithm, and service platforms. The system architecture integrates standardized data management, AI-driven analytical modules, and interoperable service interfaces to optimize pathological workflows. Key workflow improvements include standardized specimen processing, intelligent diagnostic assistance, and platform-based service integration. Furthermore, the study explores prospective application scenarios for digital intelligence pathology platforms, spanning diagnostic services, multidisciplinary consultations, medical education, scientific research, and quality control. Strategic recommendations are provided to accelerate adoption: establishing policy-guided industry standards, diversifying funding channels, strengthening professional training, advancing technological innovation, and ensuring data security with privacy protection. These measures aim to expedite the integration of digital intelligence pathology into clinical practice and support the evolution of smart healthcare.
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institution OA Journals
issn 1009-1742
language zho
publishDate 2025-04-01
publisher 《中国工程科学》杂志社
record_format Article
series 中国工程科学
spelling doaj-art-e66a5633ffad47af90a6073e1c6967ae2025-08-20T02:35:32Zzho《中国工程科学》杂志社中国工程科学1009-17422025-04-0127230431410.15302/J-SSCAE-2024.11.024Digital Intelligence Pathology Platform and Its Service PatternXiaohong Chen0Liu Liu1Yajua Niu2Xiaoliang Liu3Xiaohai Li4Jianhua Zhou5Junpu Wang61. School of Business, Central South University, Changsha 410083, China|2. Xiangjiang Laboratory, Changsha 410205, China|3. School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China|4. School of Management Science and Engineering, Hunan University of Technology and Business, Changsha 410205, China1. School of Business, Central South University, Changsha 410083, China|2. Xiangjiang Laboratory, Changsha 410205, China|3. School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China|4. School of Management Science and Engineering, Hunan University of Technology and Business, Changsha 410205, China5. Xiangya Hospital of Central South University, Changsha 410008, China|6. School of Basic Medicine, Central South University, Changsha 410008, China1. School of Business, Central South University, Changsha 410083, China|2. Xiangjiang Laboratory, Changsha 410205, China|3. School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China|4. School of Management Science and Engineering, Hunan University of Technology and Business, Changsha 410205, China2. Xiangjiang Laboratory, Changsha 410205, China5. Xiangya Hospital of Central South University, Changsha 410008, China|6. School of Basic Medicine, Central South University, Changsha 410008, China5. Xiangya Hospital of Central South University, Changsha 410008, China|6. School of Basic Medicine, Central South University, Changsha 410008, ChinaPathological diagnosis is the cornerstone for clinical diagnosis and treatment decision-making. The digital intelligence pathology platform built by integrating artificial intelligence, big data, and other information technologies has great application values, which will support the digitalization and intelligent upgrading of the pathology discipline and expand the Chinese solution of intelligent pathology. This study systematically clarifies the conceptual framework of digital intelligence pathology, identifies practical application requirements, and highlights critical challenges in its implementation. Building on proprietary research achievements, we propose a tripartite middleware architecture comprising data, algorithm, and service platforms. The system architecture integrates standardized data management, AI-driven analytical modules, and interoperable service interfaces to optimize pathological workflows. Key workflow improvements include standardized specimen processing, intelligent diagnostic assistance, and platform-based service integration. Furthermore, the study explores prospective application scenarios for digital intelligence pathology platforms, spanning diagnostic services, multidisciplinary consultations, medical education, scientific research, and quality control. Strategic recommendations are provided to accelerate adoption: establishing policy-guided industry standards, diversifying funding channels, strengthening professional training, advancing technological innovation, and ensuring data security with privacy protection. These measures aim to expedite the integration of digital intelligence pathology into clinical practice and support the evolution of smart healthcare.https://www.engineering.org.cn/sscae/EN/PDF/10.15302/J-SSCAE-2024.11.024digital intelligence pathologypathological diagnosispathological foundation modelservice patternpathologypathology department
spellingShingle Xiaohong Chen
Liu Liu
Yajua Niu
Xiaoliang Liu
Xiaohai Li
Jianhua Zhou
Junpu Wang
Digital Intelligence Pathology Platform and Its Service Pattern
中国工程科学
digital intelligence pathology
pathological diagnosis
pathological foundation model
service pattern
pathology
pathology department
title Digital Intelligence Pathology Platform and Its Service Pattern
title_full Digital Intelligence Pathology Platform and Its Service Pattern
title_fullStr Digital Intelligence Pathology Platform and Its Service Pattern
title_full_unstemmed Digital Intelligence Pathology Platform and Its Service Pattern
title_short Digital Intelligence Pathology Platform and Its Service Pattern
title_sort digital intelligence pathology platform and its service pattern
topic digital intelligence pathology
pathological diagnosis
pathological foundation model
service pattern
pathology
pathology department
url https://www.engineering.org.cn/sscae/EN/PDF/10.15302/J-SSCAE-2024.11.024
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AT xiaohaili digitalintelligencepathologyplatformanditsservicepattern
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