By being able to detect higher-risk cases quicker, the hospital can devote more resources to improve medical management outcomes

On 20 November 2024, Siriraj Piyamaharajkarun Hospital (SiPH), announced a successful transformation of its Pathology Information System (PIS) using advanced computational technologies and AI that integrates laboratory workflows, image scanning systems, and centralized data processing.

This integration establishes a cohesive approach for pathological cancer diagnosis, and lays the foundation for SiPH’s future advancements in cancer diagnostics.

The system’s automated workflows and AI-driven slide image analysis — currently under pilot testing for prostate cancer diagnosis — streamlines the identification of potentially cancerous tissues. By automatically processing and feeding disparate diagnostic results back into the system, the platform enables doctors to concentrate on high-risk cases, significantly improving diagnostic accuracy and efficiency.

According to the hospital’s Director, Digital Pathology Center, Dr Pornsuk Cheunsuchon: “Today’s success in transforming our pathology workflows and enhancing diagnostic quality will ultimately lead to more accurate cancer diagnostics, benefiting patients across Thailand and ASEAN. This achievement also unlocks new capabilities in computational pathology, paving the way for integrated, automated AI-powered diagnostics to play a pivotal role in the future of clinical care at SiPH.”

The automation also involves simplification of data entry through the use of smart forms and speech-to-text AI models to integrate information about tissue specimens with high-resolution images from slide scanners. These images undergo AI-powered analyses to yield real-time access to integrated data, allowing pathologists to quickly and accurately diagnose potentially high-risk cancer cases.

Said Anothai Wettayakorn, Managing Director, IBM Thailand, a major technology partner in the project: “This advancement addresses key challenges in computational pathology, from integrating raw data from various sources, to overcoming the limitations of processing power needed to analyze vast amounts of data and images… to (help) SiPH minimize risks, secure AI workloads at all layers, and protect data through accelerated encryption…  which will ensure better care for patients across Thailand and ASEAN.”