ABOUT US
The Problem
The ratio of doctors to patients in developing world is significantly low. The World Health Organization estimates that fewer than 2.3 health workers (physicians, nurses, and midwives only) per 1,000 would be insufficient to achieve coverage of primary healthcare needs alone.In Nigeria, this figure stands at 0.4 physicians available per 1000 population. This leads to reduced access to specialist advice and often misdiagnosis in resource scarce communities. There is a wide variation in health status and access to care within the 6 geopolitical regions with indicators generally worse in the Northern region of the country.
Our Mission
Our mission is to digitize the system of diagnosis by using of low-cost, and innovative algorithms to automatically detect medical conditions faster and to enrol medical experts both locally and around the world to remotely diagnose patients using medical images that will further facilitate patient access to specialist health care.AI Powered Diagnosis
In recent years, the use of artificial intelligence for disease classification has seen an immersive leap forward thanks to the advent of convolutional neural networks (CNNs) and steadily increasing computational power.Such CNNs enable the efficient learning of features of different diseases (local connectivity patterns directly from images of disease samples) without manual human interactions. Nowadays, machine learning algorithms employing CNNs have become state-of-the-art in various fields, including computer vision (for self-driving cars) (Krizhevsky et al., 2017) as well as medical image analysis through the use of artificial intelligence for automations (Shin et al., 2016, Pinto et al., 2016).
Especially in medicine, considerable advances have been made for developing automated diagnostic image analysis systems for the precise detection of diseases. Several different artificial intelligence systems have been used recently in many countries in Europe, Asia and also the USA for classifying various types of diseases accurately and faster, which includes different types of cancer (Seung Seog et al., 2018) and also correctly diagnosing diseases such as TB without any human interactions (Hwang et al., 2018).
The aim of this project, is to develop a low-cost, efficient and accurate online platform for remote and automatic diagnosis of different diseases and also to serve as a third eye to the medical experts.