New-age technologies-driven social innovation: What, how, where, and why?
Social innovation (SI) offers a sustainable solution to prevalent social issues/problems and
is typically developed and deployed by a varied set of people from the society adopting a top …
is typically developed and deployed by a varied set of people from the society adopting a top …
Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future
Abstract Machine and deep learning techniques are prevalent in the medical discipline due
to their high level of accuracy in disease diagnosis. One such disease is malaria caused by …
to their high level of accuracy in disease diagnosis. One such disease is malaria caused by …
XGBoost model for chronic kidney disease diagnosis
A Ogunleye, QG Wang - IEEE/ACM transactions on …, 2019 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is a menace that is affecting 10 percent of the world
population and 15 percent of the South African population. The early and cheap diagnosis of …
population and 15 percent of the South African population. The early and cheap diagnosis of …
Deep learning for smartphone-based malaria parasite detection in thick blood smears
Objective: This work investigates the possibility of automated malaria parasite detection in
thick blood smears with smartphones. Methods: We have developed the first deep learning …
thick blood smears with smartphones. Methods: We have developed the first deep learning …
Malaria parasite detection using deep learning algorithms based on (CNNs) technique
MHD Alnussairi, AA İbrahim - Computers and Electrical Engineering, 2022 - Elsevier
Malaria is a life-threatening disease caused by female anopheles mosquito bites that are
prevalent in many regions of the world. We introduce a deep convolutional neural network …
prevalent in many regions of the world. We introduce a deep convolutional neural network …
Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning
D Das, R Vongpromek, T Assawariyathipat… - Malaria Journal, 2022 - Springer
Abstract Background Microscopic examination of Giemsa-stained blood films remains the
reference standard for malaria parasite detection and quantification, but is undermined by …
reference standard for malaria parasite detection and quantification, but is undermined by …
Computer-automated malaria diagnosis and quantitation using convolutional neural networks
The optical microscope remains a widely-used tool for diagnosis and quantitation of malaria.
An automated system that can match the performance of well-trained technicians is …
An automated system that can match the performance of well-trained technicians is …
Diagnosing Malaria Patients with Plasmodium falciparum and vivax Using Deep Learning for Thick Smear Images
We propose a new framework, PlasmodiumVF-Net, to analyze thick smear microscopy
images for a malaria diagnosis on both image and patient-level. Our framework detects …
images for a malaria diagnosis on both image and patient-level. Our framework detects …
Artificial intelligence and sustainable development in China
S Liengpunsakul - The Chinese Economy, 2021 - Taylor & Francis
This paper examines artificial intelligence (AI) and sustainable development in China. The
Chinese government has developed ambitious policies for global leadership in the field of AI …
Chinese government has developed ambitious policies for global leadership in the field of AI …
Development of a low-cost robotized 3D-prototype for automated optical microscopy diagnosis: An open-source system
A Dantas de Oliveira, C Rubio Maturana… - Plos One, 2024 - journals.plos.org
In a clinical context, conventional optical microscopy is commonly used for the visualization
of biological samples for diagnosis. However, the availability of molecular techniques and …
of biological samples for diagnosis. However, the availability of molecular techniques and …