Deep learning method for malaria parasite evaluation from microscopic blood smear-Reference-Cited by-同舟云学术

Deep learning method for malaria parasite evaluation from microscopic blood smear

Published:2025-05 Issue: Volume:163 Page:103114
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Dahiya Abhinav,Raghuvanshi Devvrat,Sharma Chhaya,Joshi Kamaldeep,Nehra Ashima,Sharma Archana,Jangra Radha,Badhwar Parul,Tuteja Renu,Gill Sarvajeet S.,Gill Ritu

Funder

Department of Biotechnology, Ministry of Science and Technology, India

Science and Engineering Research Board

University Grants Commission

Council of Scientific and Industrial Research, India

Publisher

Elsevier BV

Reference82 articles.

1. Machine and deep learning methods in identifying malaria through microscopic blood smear: A systematic review;Sukumarran;Eng Appl Artif Intell,2024

2. Performance analysis of deep learning algorithms in diagnosis of malaria disease;Hemachandran;Diagnostics,2023

3. Human plasmodium vivaxdiversity, population structure and evolutionary origin;Rougeron;PLoS Negl Trop Dis,2020

4. Artificial intelligence-based approaches for detection and classification of different classes of malaria parasites using microscopic images: a systematic review;Kakkar;Arch Comput Methods Eng,2023

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1. Multi-Modal Deep Learning for Malaria Diagnosis: Integrating CNNs and Vision Transformers for Enhanced Parasite Detection;2025 Third International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2025-05-21