Journal of Health & Medical Informatics

Department of Computer Sciences, University of Lagos, Lagos, Nigeria

Publications

• Review Article   
  A Deep Learning based Clinical Decision Support System for Malaria Diagnosis and Detection
  Author(s): Alamu Femi O, Abiodun Adeyinka O* and Jinadu Ahmad Adekunle
  
  Malaria remains one of the major challenges faced in healthcare in Africa, especially in Nigeria with an estimated 300,000 children killed by malaria annually. Apart from low doctor to patient ratio in Nigeria, poor diagnosis is another major cause of increase in malaria death rate. This research developed a Clinical Decision Support System (CDSS) to detect malaria infected patients using deep and machine learning technique. For this, we developed an in-depth learning method from camera captured Giemsa-stained thin blood smear slides from 150 Plasmodium Falciparum infected and 50 non-infected patients from a national center for biomedical communications. The dataset contains 27,558 cell images with equal number of malaria infected and non-infected cell images which are 13,779. The architecture of the proposed model predicted patient’s malaria s.. Read More»
  DOI: DOI: 10.37421/2157-7420.2022.13.427

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