Best Ideas 2018 features all the nominated entries submitted to the Youth Citizen Entrepreneurship Competition under ‘Submit your Idea’ category. All the entries consist of innovative solution or proposition for an enterprise that champions the Sustainable Development Goals. They can be on the conceptual, planning, or start-up stage. If you want to know the 10 finalists in this category, click HERE
UTI(URINARY TRACT INFECTION) DIAGNOSIS USING SMART PHONE
Explain your idea in details:
Urinary tract infection (UTI), defined as a condition in which bacteria are established and multiplying within the urinary tract is the most common infection experienced by humans. It is among the commonest causes of febrile illness in children of less than five years of age in Sub-Saharan Countries [Magufi 2016]. Besides, it is the most common bacterial infections during pregnancy accounting for approximately 10% of hospital visits by women[Millar 1997]. Thus early-diagnosis and appropriate treatment of UTI is essential in order to avoid long term complications. However, most rural areas in development countries lack medical professionals and laboratory facilities to enable timely UTI diagnosis. Thus the approach is to build a mobile application with Machine Intelligence to diagnose UTI , the way through will be training an algorithm from thousands of Urine Images sample to be collected from hospitals. The algorithm will be trained from thousands of data and validated and testing on different set of data so that the model obtained from the trained data and validation data will be able to generalize i.e to be able to predict collect on the new data ( urine image) .The model that will attain the greatest accuracy will be embedded on the mobile application and deployed with it.
Expected impact of your idea on sustainable development
The target is to have a smart-phone application that can diagnose UTI with high precision. The achievement will increase availability of service to people who in most cases find difficult to reach hospital for urine checkup or find difficult to meet hospital cost. Apart from this it will further stimulate community to adapt the new way of diagnosing UTI and not depending on the tradition means. The success of the ideas depends highly on selection of good algorithm to study the problem(UTI diagnosis) as well as acquisition of clear and clean data (Urine sample Images ) to train algorithm that will be deployed on the mobile application and the measure which will determine the success of the idea will be user satisfaction on using the mobile application
Plans for implementation and sustainability
Existing system has many challenges during the process of diagnosing UTI in hospital or Labs such as long waiting time and high cost consumed during UTI testing. Thus we aim to develop a mobile application that uses Machine Intelligence to diagnose UTI based on different model and algorithm trained to accomplish UTI measurement . The tool will be efficient, time friendly,cost effective and simple to use. The intention is the mobile application to be free purchased on the Google play store so that anyone can purchase the application but it should be required to pay for the services when diagnosing UTI, and the payment is intended to be as cheap as possible in order no one should fail to acquire service. For the complete implementation of this idea we require at least a total of US dollar 2500 for labor force and other facilities .
My name is Yakobo Yakubona ,I was born on 3rd June of 1991 in Mwanza region located Northern Tanzania, East Africa . I received an advanced secondary education at Sengerema high school where I studied Physics, Advanced Mathematics and Geography between the year 2011 and 2013. I was enrolled at the University of Dodoma in 2013 to pursue a Bachelor degree in Telecommunication Engineering which I graduated in 2017. I started programming while I was a third year students and most of the interested language was Python ,I developed a tool to collect household aggregate power consumption using Python programming and Internet of Things(IoT ) and the tools was presented as the final year project .While I was about to finish my study at the university, I attended a workshop at the University of Dodoma that was aimed to equip young students on Python programming, Machine Learning and Deep Learning, at this time I participated fully and given the chance to join PythonTz which is the corporation of Python programmers in Tanzania .Currently I am working with Parrot.ai company which is the startup company in artificial intelligence . After joining Parrot.ai I have attended a total of two workshops and summer schools on Machine Learning and the most recently one was a Data Science Africa at Dedan Kimath University of Technology (Nyeri Kenya) on June,2018 aimed to train trainers on Data Science. Following the participation of different workshops I gained insight of how powerful Machine Learning as it can solve complex problems that seem very complex for classical programming to achieve ,and one of the common problem that we has identified is the use of Machine Learning to Diagnose Urinary tract Infections .