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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Combining Clinical Symptoms and Patient Features for Malaria Diagnosis: Machine Learning Approach
Martina Mariki, Elizabeth Mkoba, Neema Mduma
Applied Artificial Intelligence (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 19

Showing 19 citing articles:

Performance Analysis of Deep Learning Algorithms in Diagnosis of Malaria Disease
K. Hemachandran, Areej Alasiry, Mehrez Marzougui, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 534-534
Open Access | Times Cited: 57
Application of hybrid capsule network model for malaria parasite detection on microscopic blood smear images
S. Aanjan Kumar, Monoj Kumar Muchahari, S. Poonkuntran, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 6
Microscopic parasite malaria classification using best feature selection based on generalized normal distribution optimization
Javeria Amin, Muhammad Almas Anjum, Abraz Ahmad, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1744-e1744
Open Access | Times Cited: 5
Machine Learning Techniques for Predicting Malaria: Unpacking Emerging Challenges and Opportunities for Tackling Malaria in Sub-saharan Africa
Elliot Mbunge, Richard C. Milham, Maureen Nokuthula Sibiya, et al.
Lecture notes in networks and systems (2023), pp. 327-344
Closed Access | Times Cited: 10
A Machine Learning Framework for Length of Stay Minimization in Healthcare Emergency Department
Daniel Asuquo, Imeh Umoren, Francis B. Osang, et al.
Studies in Engineering and Technology (2023) Vol. 10, Iss. 1, pp. 1-1
Open Access | Times Cited: 7
Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging
Corin F. Otesteanu, Reto Caldelari, Volker T. Heussler, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 24, pp. 334-342
Open Access | Times Cited: 1
Malaria Disease Prediction Based on Convolutional Neural Networks
Dhrgam Al Kafaf, Noor N. Thamir, Samara S. AL-Hadithy
Journal of Applied Engineering and Technological Science (JAETS) (2024) Vol. 5, Iss. 2, pp. 1165-1181
Open Access | Times Cited: 1
Enhancing the Interpretability of Malaria and Typhoid Diagnosis with Explainable AI and Large Language Models
Kingsley Attai, Moses E. Ekpenyong, Constance Amannah, et al.
(2024)
Open Access | Times Cited: 1
Prediction of malaria positivity using patients’ demographic and environmental features and clinical symptoms to complement parasitological confirmation before treatment
Taiwo Adetola Ojurongbe, Habeeb Abiodun Afolabi, Kehinde Adekunle Bashiru, et al.
Tropical Diseases Travel Medicine and Vaccines (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 4
Towards digital diagnosis of malaria: How far have we reached?
Sana Aqeel, Zafaryab Haider, Wajihullah Khan
Journal of Microbiological Methods (2022) Vol. 204, pp. 106630-106630
Closed Access | Times Cited: 4
Machine learning approach to identify malaria risk in travelers using real-world evidence
Pedro Emanuel Fleitas, Leire Balerdi-Sarasola, Daniel Camprubi Ferrer, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28534-e28534
Open Access
Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endemic Areas of Tanzania
Martina Mariki, Neema Mduma, Elizabeth Mkoba
Progress in IS (2024), pp. 53-69
Closed Access
Enhancing the Interpretability of Malaria and Typhoid Diagnosis with Explainable AI and Large Language Models
Kingsley Attai, Moses E. Ekpenyong, Constance Amannah, et al.
Tropical Medicine and Infectious Disease (2024) Vol. 9, Iss. 9, pp. 216-216
Open Access
Prediction of malaria positivity using patients’ demographic and environmental features and clinical symptoms to complement parasitological confirmation before treatment
Taiwo Adetola Ojurongbe, Habeeb Abiodun Afolabi, Kehinde Adekunle Bashiru, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Malarial Diagnosis with Deep Learning and Image Processing Approaches
Mogalraj Kushal Dath, Nahida Nazir, Amita Dhankhar, et al.
International Journal on Recent and Innovation Trends in Computing and Communication (2023) Vol. 11, Iss. 5s, pp. 210-222
Open Access | Times Cited: 1
Prediction of malaria outcomes using patients’ demographical, environmental and clinical features
Taiwo Adetola Ojurongbe, Habeeb Abiodun Afolabi, Sunday Babatunde Akinde, et al.
Research Square (Research Square) (2023)
Open Access
Analysing the ML and DL-based Models for Predicting Malarial Fever Prior to Clinical Trial
Md. Robiul Islam, Tanjina Nur Jeba, Md. Sabab Zulfiker, et al.
2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (2023)
Closed Access
Improving malaria prediction with ensemble learning and robust scaler: An integrated approach for enhanced accuracy
Azka Khoirunnisa, Nur Ghaniaviyanto Ramadhan
JURNAL INFOTEL (2023) Vol. 15, Iss. 4, pp. 326-334
Open Access
An investigation of ICT-based malaria intervention framework for rural communities
Elliot Mbunge
(2022)
Open Access
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