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InformAI's TransplantAI Featured As a V7 Case Study

InformAI was featured in a V7 software case study that outlines how InformAI used V7 to build an organ volume estimation model achieving 97% accuracy. The case study outlines the issue of organ size mismatch in transplantation, which can lead to organ non-use and poor patient outcomes. InformAI leveraged V7's capabilities to develop medical workflows for labeling DICOM files containing organ scans used to create ground truth for our product, TransplantAI, a comprehensive, integrated AI informatics dashboard that supports clinical workflow for organ transplants.

V7 had all the capabilities we were looking for including a user-friendly interface, browser access, ease of collaboration, and necessary data security features.

Read the full case study here:

About V7

V7 is led by Alberto Rizzoli and Simon Edwardsson, two-time co-founders who brought with them a team of machine learning engineers and researchers from Google, Graphcore, Onfido, Entrepreneur First, Tractable and more. Within half a year of implementing V7, customers report 33% faster release of models and 25% reduction in errors on average. The platform now handles over 1 petabyte of AI training data, making it one of the largest libraries of human knowledge applied to images spanning radiology, engineering, and biopharma in existence. The founders previously founded Aipoly, a computer vision app that helped the blind to understand their surroundings by recognising and audibly describing objects from a mobile phone. Aipoly won the CES Best of Innovation Award two years running (2017/18) and was the world’s first commercial use of a convolutional neural network for object recognition running in real-time on an iPhone.


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