Xiangya Hospital of Central South University is a prestigious Class-A Grade-3 general hospital founded in 1906 in Changsha, known as one of China's leading medical centers with a century-old history rooted in the Yale-China relationship.
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Case Study

Case Study: Xiangya Hospital, Central South University | KFBIO

By Published On: 11/12/2025

 

Background

Xiangya Hospital of Central South University is a national Class-A tertiary hospital and one of China’s most prestigious medical institutions.
It is the national key discipline for pathology, a major clinical center for cervical cytology diagnosis, and the regional diagnostic hub for Hunan Province.

Challenges

  • Heavy Diagnostic Workload: Traditional microscopic diagnosis of cervical smears was time-consuming, and the increasing number of screening cases placed heavy pressure on pathologists.
  • Regional Imbalance: Uneven resource distribution made it difficult for county-level hospitals to obtain expert consultation in a timely manner.
  • Efficiency Gap: Manual workflows and high sample volumes limited turnaround speed and diagnostic consistency.
  • Data Silos: Lack of centralized data management hindered collaboration and case sharing between hospitals.

Solutions

Through cooperation with KFBIO, Xiangya Hospital deployed an AI-assisted cervical cytology diagnosis platform combined with a regional telepathology consultation system.

  • Introduced AI recognition algorithms for automated identification of cervical epithelial and atypical cells, improving diagnostic efficiency.
  • Integrated telepathology modules that enable remote slide viewing, AI pre-screening, and online expert review.
  • Connected county and municipal hospitals to the Xiangya diagnostic center, enabling cloud-based consultations and real-time feedback.

Results & Benefits

  • AI-Assisted Cytology Diagnosis: AI algorithms replaced manual pre-screening for liquid-based cytology, boosting pathologists’ efficiency and reducing diagnostic fatigue.
  • High-Volume Processing: The system handles over 300 cervical cytology slides daily, totaling over 100,000 slides annually.
  • Regional Collaboration: The platform links multiple hospitals, allowing real-time case consultation and centralized expert review.
  • Time Efficiency: Diagnostic turnaround for remote frozen sections has been shortened to under 6 minutes, and regional AI-assisted results can be returned within 2–3 hours.

“KFBIO’s scanning system meets all our clinical requirements — both speed and accuracy. Once we tried it, we knew this was the right solution.”
— Dr. Hu Jie, Director of Pathology, Xiangya Hospital

Outcome

The integration of AI cytology diagnosis and telepathology network enables Xiangya Hospital to provide high-efficiency, standardized diagnostic services across the region.
This system has significantly increased diagnostic capacity, reduced manual workload, and strengthened remote collaboration, serving as a model for AI-empowered regional pathology networks.

Keywords

AI Diagnosis · Cervical Cytology · Telepathology · Regional Collaboration · Smart Pathology Network · Workflow Efficiency

Written by : Wang, Sibo

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