HealthCare Global Enterprises Ltd (HCG), an Indian specialty healthcare services hospital focused on oncology has deployed Sigtuple’s AI100 to equip the Hematopathology labs across its network with AI-powered screening solutions for cancer detection and disease management.
The screening tool enables AI-assisted digital hematopathology to automate the manual microscopy (screening) process across its network.
As manual microscopy is still the standard in diagnosing several critical disorders like cancers, infections, etc., in the absence of a pathologist at site in laboratories outside urban areas, these samples need to be shipped to central reference laboratories for review.
Apart from the logistic challenges and associated delays in turnaround times, there is also limited expertise available for providing high quality diagnostics at remote locations.
“AI-assisted digital scanning technology has indeed emerged as a game-changer in cancer care. Sigtuple’s best-in-class solution has brought remarkable precision to HCG’s Hematopathology diagnostic capabilities. The automation of key processes and optimization of logistics by virtue of this pioneering technology is a distinct value-add for HCG, given our overarching goal of serving the larger cause of patients through enhanced clinical outcomes,” stated Dr B.S. Ajaikumar, Executive Chairman, HCG.
World over, it is strongly believed that artificial intelligence assisted digital scanning technology is the way forward for pathology. Digital scanning technology makes it possible for pathologists to review samples remotely, without having to ship them to the reference laboratory, as the digital conversion can happen at site.
This collaboration is expected to significantly reduce the turnaround time, standardise reporting quality and increase efficiency multi-fold. Further, this solution will enable pathologists to collaborate seamlessly across geographies thereby ensuring that every HCG centre will now get access to expertise across the network within seconds. BW Businessworld