05/03/2026
In neurotrauma, triage happens in real time across high-volume emergency workflows.
The question is not whether AI can detect hemorrhage or fracture.
It is whether AI can be integrated into clinical systems responsibly with radiologist oversight, governance safeguards, and measurable validation.
In the 𝐂𝐨𝐦𝐩𝐞𝐧𝐝𝐢𝐮𝐦 𝐨𝐧 𝐑𝐞𝐚𝐥 𝐖𝐨𝐫𝐥𝐝 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐇𝐞𝐚𝐥𝐭𝐡, released at the 𝐈𝐧𝐝𝐢𝐚 𝐀𝐈 𝐈𝐦𝐩𝐚𝐜𝐭 𝐒𝐮𝐦𝐦𝐢𝐭 2026 in partnership with the 𝐖𝐨𝐫𝐥𝐝 𝐇𝐞𝐚𝐥𝐭𝐡 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧, 𝘋𝘳. 𝘈𝘳𝘫𝘶𝘯 𝘒𝘢𝘭𝘺𝘢𝘯𝘱𝘶𝘳* authors the chapter:
“𝐀𝐈-𝐒𝐮𝐩𝐩𝐨𝐫𝐭𝐞𝐝 𝐍𝐞𝐮𝐫𝐨𝐢𝐦𝐚𝐠𝐢𝐧𝐠: 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐭𝐡𝐞 𝐓𝐫𝐢𝐚𝐠𝐞 𝐨𝐟 𝐀𝐜𝐮𝐭𝐞 𝐒𝐭𝐫𝐨𝐤𝐞 𝐚𝐧𝐝 𝐇𝐞𝐚𝐝 𝐈𝐧𝐣𝐮𝐫𝐲.”
This chapter presents a structured use case of 𝐍𝐞𝐮𝐫𝐚𝐥𝐀𝐬𝐬𝐢𝐬𝐭 integration with 𝐑𝐀𝐃𝐒𝐩𝐚, Telerad Tech’s cloud-based RIS–PACS workflow supporting triage of intracranial hemorrhage, midline shift, dense MCA sign, and skull fractures under defined validation conditions.
Importantly, the model is positioned as decision support, not as an independent diagnosis tool.
This approach reflects how 𝐈𝐦𝐚𝐠𝐞 𝐂𝐨𝐫𝐞 𝐋𝐚𝐛 supports neuroimaging AI programs.
We have contributed to 10+ AI and SaMD programs across critical 𝐓𝐁𝐈 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 — intracranial hemorrhage, midline shift, and skull and spine fracture detection.
Our work focuses on expert-defined ground truth, structured reader workflows, and MRMC study design, the validation architecture that determines whether an AI model withstands regulatory and clinical scrutiny.
📄 Read the full chapter here: 🔗https://d19ob9sqegt2wc.cloudfront.net/stage/uploads/AI_Health_Compendium_2026_5604af298c.pdf
* 𝘋𝘳. 𝘈𝘳𝘫𝘶𝘯 𝘒𝘢𝘭𝘺𝘢𝘯𝘱𝘶𝘳, 𝘊𝘩𝘪𝘦𝘧 𝘙𝘢𝘥𝘪𝘰𝘭𝘰𝘨𝘪𝘴𝘵 𝘢𝘯𝘥 𝘊𝘰-𝘍𝘰𝘶𝘯𝘥𝘦𝘳, 𝘐𝘮𝘢𝘨𝘦 𝘊𝘰𝘳𝘦 𝘓𝘢𝘣, 𝘢𝘯 𝘦𝘯𝘵𝘪𝘵𝘺 𝘰𝘧 𝘛𝘩𝘦 𝘛𝘦𝘭𝘦𝘳𝘢𝘥 𝘎𝘳𝘰𝘶𝘱