Xolani Health

01

JICA

Team Xolani health with
Senior Vice President
Japan International Cooperation Agency (JICA)
during her recent visit to Abuja.

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02

Techstars

Xolani Health was selected as
one of the 12 startups to participate in the
Techstars Tel-Aviv accelerator program in March
2023.

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02

IRCAI

We are thrilled to announce that Xolani Health
has been named one of the most promising
Artificial Intelligence startups on the
IRCAI Global Top 100 international list.

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Revolutionising Radiology in Africa

Xolani Health provides AI-assisted tools that enables a collaborative ecosystem for healthcare workers.

Tele-Radiology

Our proprietary imaging and teleradiology solution is designed with real-time collaboration features, providing hospitals with convenient access to radiologists and optimizing the interpretation process,

Medical Excellence

We are providing AI solutions to help modernize and digitize clinical operations and get more value from the ever-expanding health data.

AI Diagnosis

The XolaNet models have been trained to identfy several diseases with just a scan from images.

Speed and Accuracy

With our solution, speed and acuracy of diagnosis have been improved.

XolaNets

We have developed several AI models – XolaNets for detecting Covid 19 Virus, Breast Cancer, Malaria, Bone Defects, Ejection Fraction of the Heart and more.

Covid 19
We found a way of detecting Covid 19 from the X-ray of the human chest. Here, an X-ray image of a human chest is passed through our XolaNets to detect if the he/she is covid 19 Positive or Negative.
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Breast Cancer (Mammography)
This Model uses X-ray images of the human female Breast that have been scanned cancerous. These X-ray images are again, passed through our XolaNets to predict it state of being either benign or malignant
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Malaria
This is a demonstration of how we used Artificial Intelligence in detecting Malaria from blood samples of the humans. Here, a microscopic thin blood smear images is passed through our XolaNets to detect if there is presence of Malaria parasite or not
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Cardiomyopathy
This demonstration was made on Echo-cardiogram videos. Here, images (frames) from a video of an echo-cardiogram is extracted and passed through our XolaNets to detect the Ejection Fraction - (EF) of the heart.
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Introducing Xolani Bridge

Xolani Bridge

XOLANI BRIDGE is our proprietary imaging and teleradiology solution designed to integrate seamlessly into clinical workflows. With real-time collaboration features, our platform optimizes the interpretation process, providing hospitals with convenient access to radiologists. Through our innovative technology, we aim to enhance medical imaging services, reduce delays, and drive better patient outcomes. Our online platform connects hospitals with a global community of radiologists, ensuring timely access to accurate interpretations and improving patient outcomes.