Jakarta, INTI - The development of artificial intelligence (AI) technology is increasingly showing its important role in the world of health. One of the latest breakthroughs comes from the National Research and Innovation Agency (BRIN), which reveals that AI technology is now able to help diagnose malaria more accurately and quickly, especially in areas with high cases such as Papua.
Based on data from the Ministry of Health Republic Indonesia, Papua is listed as the region with the highest malaria caseload in Indonesia. In fact, by 2024, this province accounts for around 88 percent of the total national malaria cases. The disease, which is transmitted through the bite of the Anopheles mosquito, is still a serious challenge, especially in Eastern Indonesia such as Papua, West Papua, Maluku, and East Nusa Tenggara.
AI Technology for More Accurate Diagnosis
Principal Research Scientist at BRIN's Eijkman Molecular Biology Research Center, Puji Budi Setia Asih, explained that one of the main obstacles in malaria treatment is the limited diagnosis facilities at first-level health services such as Community Health Centers. Currently, malaria detection still relies on microscopic examination and rapid diagnostic tests (RDTs), which have limitations in terms of sensitivity and accuracy.
“An artificial intelligence-based microscopic approach will greatly help improve the sensitivity and accuracy of diagnosis. This is an important prerequisite towards malaria elimination,” Puji explained in her statement, Thursday, May 8, 2025.
AI in malaria diagnosis was developed using data from various regions in Indonesia, allowing the system to recognize various species of malaria parasites. This technology, said Puji, is crucial in determining treatment and assessing the severity of the disease.
Research Collaboration and Challenges Faced
This research was developed by BRIN in collaboration between the Eijkman Molecular Biology Research Center and the Research Center for Artificial Intelligence and Cyber Security (PRKAKS). This diagnosis system uses a Plasmodium parasite recognition algorithm that causes malaria.
However, the development of this technology is not free from challenges. One of them is the absence of standardization in the coloring of blood preparation images to be analyzed. This makes the AI system need to be trained with various variations to remain accurate.
Head of BRIN's PRKAKS, Anto Satriyo Nugroho, explained that the AI system works by analyzing microscopic images of thin and thick blood preparations. The AI then extracts morphological and geometric features of blood cells to identify malaria infection.
“The changing shape of the parasite during its life cycle is a challenge in developing this system. But we are optimistic that continued research will produce a much-needed diagnostic tool to support malaria eradication,” he said.
AI for Mosquito and Larva Detection
Not only for diagnosis, Puji also revealed the potential of AI to support the control of malaria vectors, namely Anopheles mosquitoes. By combining AI and drone technology, mosquito breeding sites can be mapped more efficiently. This allows for quick interventions, such as larval control in places detected as sources of transmission.
AI can also help identify the morphology of mosquitoes to distinguish the malaria-causing species from other mosquito species, before proceeding with laboratory testing.
Towards Malaria Elimination 2030
BRIN's research is in line with the national target to eliminate malaria by 2030. In addition to collaboration between BRIN's internal research centers, this research is also supported by cooperation with various parties, such as domestic and foreign universities, WHO, UNICEF, and the Ministry of Health.
With the support of AI technology and cross-sector collaboration, it is hoped that Indonesia can immediately reduce the incidence of malaria, especially in areas that have been difficult to reach by health facilities.
Conclusion
Advances in artificial intelligence (AI) technology are increasingly playing an important role in global health. In Indonesia, especially eastern regions such as Papua that still face a high malaria caseload, AI innovations provide new hope in improving the effectiveness of disease diagnosis and treatment. With the ability to automatically analyze blood samples and recognize the morphology of the mosquito that causes malaria, AI is a strategic tool in the national malaria elimination effort towards the 2030 target. Collaborative research, regulatory support, and utilization of data-driven technology are the keys to successful malaria eradication in the future.
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