A Rwandan scientist, Audace Nkeshimana, who graduated from Massachusetts Institute of Technology (MIT), an elite US-based university, is looking to make radiology services remotely accessible to Rwandans by using Artificial Intelligence (AI).
Nkeshimana says he looks to “democratize” the medical imaging diagnostics in Rwanda by making it possible for radiologists to digitally analyze patients’ images remotely, aided by the platform’s different assistive capabilities that are powered by AI.
Insightiv’s main product is a Tele-radiology platform assisted by AI that allows medical imaging specialists like radiologists to receive and interpret medical images remotely, without being required to travel to medical imaging facilities.
“This is very relevant in developing countries where there is not a high number of radiologists. Compared to the United States or Europe where there are about 100 radiologists for every million of the population, Rwanda only has 12 radiologists in a population of 13 million people, which is less than 1 radiologist per million,” Nkeshimana said.
Nkeshimana and his engineering team have so far managed to build a system that can handle different critical medical imaging modalities such as CT, MRI, X-Ray, and has different capabilities such as workflow management, reporting, and is able to interoperate with third-party medical imaging solutions such as more advanced medical imaging viewers, as well as being able to retrieve medical images from pre-existing Picture Archiving and Communications Systems (PACS).
He believes that hospitals and clinics that will work with his startup do not need to hire radiologists, since they will be referring such cases to Insightiv’s radiologists.
“In addition, the reduction in waiting time for patients means that we can help hospitals avoid long lines and cluttered hospital rooms that are usually occupied by patients who cannot get treated yet because we are waiting for a diagnosis.
Currently, the startup’s system is still undergoing the regulatory process in Rwanda and has not been used commercially yet, however, it has been demonstrated to different potential customers both in private hospitals, public healthcare institutions, and according to Nkeshimana, there has been good interest in it.
“The need and willingness to work with Insightiv and pay for Insightiv’s services have been clear from the beginning, as we already have letters of intent and agreements from some hospitals to work with us once our services are launched commercially,” he said.
“Surprisingly, there has also been demand from African countries, and we believe that we will be able to commercialize the services by the time we are cleared,” he added.
While developing Insightiv, Nkeshimana’s team has worked with 3 local radiologists since the middle of 2020, especially for advice about different components of the solution.
“These radiologists have been very critical in giving us feedback on different components of the system, which has allowed us to refine the functionality provided by the system, as well as to add functionality that is generally expected in modern medical imaging systems,” Nkeshimana said.
He says Insightiv can be trusted as far respecting patients’ privacy and medical standards are concerned.
“We are not taking any shortcuts with regards to respecting patients’ privacy as well as meeting clinical standards expected from medical diagnostics services. We are therefore committed to working with regulatory authorities in both the technology and healthcare sector to ensure that we have the mechanisms in place to protect patients and all users of our systems while ensuring that we deliver the best care possible,” he said.
He also says the solution is “a better opportunity for radiologists” since it will allow them to work more productively by not worrying about going to the hospitals, as they can diagnose patients remotely with aid of different assistive capabilities powered by Artificial Intelligence.
“Radiologists will be able to diagnose patients faster. In addition, radiologists will be able to diagnose patients from different hospitals and increase their customer base as a result,” he said.
“Faster diagnosis means patients will be diagnosed and treated sooner. This will be life-saving for patients who require critical care for survival,” he added.
Nkeshimana graduated from MIT in May 2020 with a bachelor’s degree in Computer Science and Engineering, and a minor in economics.
He has extensive industry background from Silicon Valley at Google and Apple in the areas of Machine Learning and Infrastructure, as well as extensive research expertise in Artificial Intelligence Fairness and Human-Computer Interaction.
His work in Healthcare AI has been published in world-class journals such as Frontiers in Artificial Intelligence and is one of the authors of the MIT OpenCourseWare class that focuses on Machine Learning Fairness for International development.