As a radiologist with 20 years of experience, Naidoo was already familiar with trend recognition, and she may see without delay how AI can be used in industry to access diagnostic images. The flame was lit and in 2019, along with her husband, Terence Naidu, and Andrei Migachev, Naidoo introduced Envisionit Deep AI, a fitness technology startup that uses AI to meet the demand for diagnostic imaging.
Envisionit Deep AI is now on track for expansion thanks to a $1. 65 million investment from New GX Ventures SA, a joint venture between New GX Capital, RMB Ventures and GIIG Africa. Start-up awards.
“We have this exciting purpose of combining the generation of breakthroughs like synthetic intelligence with radiology and we need the way radiologists look, interpret images and make diagnoses,” said Naidoo, who is also the company’s chief executive.
Hybrid solution
The startup has a suite of products it plans to expand beyond South Africa, adding the Radify AI platform, which it says ensures fast, accurate, quality and affordable medical imaging diagnosis, which is critical for early diagnosis and disease remedy.
“Radify AI obtained approval from the South African Health Products Regulatory Association. But we need to approve globally and that’s why we’re busy with FDA and European Medical Agency approval,” Naidoo said.
Naidoo says the ultimate purpose of Envisionit Deep AI is to overload the fitness system, especially in Africa, where investments in infrastructure and human resources remain abysmal.
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The data show that the doctor-to-patient ratio in sub-Saharan Africa is one of the lowest in the world, an even worse ratio for specialist doctors. In radiology, the shortage of human resources is such that the ratio of radiologists to population in Kenya, for example, is 1:389,255, while in Nigeria it is 1:566,000.
This shortage of radiologists is Naidoo’s driving force in making Radify AI available to everyone, in peri-urban and rural areas, and what prompted the startup to build a hybrid solution.
She says Radify AI can be deployed anywhere, “whether it’s in a first-world environment or in a rural clinic that may not have excellent broadband capacity or the most productive infrastructure. . . Because the very concept of our product is to democratize diagnostic imaging, and we will not democratize if we lack answers that can pass to rural areas. “
The product at the startup’s premises can be incorporated with devices such as X-ray machines to provide point-of-care diagnosis and treatment. They will also offer tele-radiology for patients requiring radiology reports.
“Usually, an X-ray takes X-rays, and then patients come home and collect the effects later, after several months. Delayed diagnosis means diseases can still progress. We eliminate that backlog, because when you know what it’s about, you treat it quickly,” Naidoo said, adding that they plan to introduce their responses in South Africa’s mining sector, where workers are most at risk of contracting TB.
The startup started from the construction of models for the interpretation of chest x-rays, capable of detecting another 25 pathologies, to which are added tuberculosis, breast cancer and pneumonia, the leading cause of death among children under five years of age in Africa.
That platform, Naidoo said, proved beneficial, especially during the COVID pandemic, when Envisionit Deep AI introduced a product that can stumble into COVID pneumonia from chest X-rays in less than 25 millimoments. This was implemented to improve the power of a 700-bed hospital in South Africa’s Northern Cape province, which only had one radiologist. Naidoo says it has also been used in several extensive care sets for triage, especially at the peak of the pandemic.
The startup says that while the volume of data it processes is comprehensive, it ensures that its models are made up of anonymized, quality data from around the world and from diverse ethnic groups.
The data can also be reviewed through radiologists who employ a validation tool that gives them some assurance that the product is working properly; and get their feedback and feedback, which allowed the implementation of the accuracy of their models.
Envisionit Deep AI recently launched a computer-based education style (an edtech tool) to keep doctors informed about radiology skills.
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