Related Experiment Video
Updated: Sep 20, 2025
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
Published on: October 27, 2023
[The future is already here and the wave is coming: progress and challenges in the research and application of
1National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu 214064, China.
Abstract:
The rapid rise and fast development of artificial intelligence (AI) has brought unprecedented opportunities and challenges to all sectors, including disease prevention control. Malaria is one of the world's most devastating infectious diseases. This article summarizes the advances in the research and application of AI-empowered malaria control programmes, analyzes key challenges during the implementation of malaria control programmes, and proposes future development directions and research proprieties, so as to provide insights into facilitating the translation of AI-driven strategies in global infectious disease control efforts.
More Related Videos
08:22IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae
Published on: January 15, 2020
15:03Building a Better Mosquito: Identifying the Genes Enabling Malaria and Dengue Fever Resistance in A. gambiae and A. aegypti Mosquitoes
Published on: July 4, 2007
