TEMPO.CO, Jakarta - The automated AI-based malaria diagnosis system developed by the National Research and Innovation Agency (BRIN) will be able to recognize parasites from microscopic blood smear images. Anto Satriyo Nugroho, a researcher from the Center for Artificial Intelligence and Cyber Security Research (PR-KAKS) at BRIN, said that this technology aimed to expedite diagnosis and improve its accuracy, especially in endemic areas.
"Our main goal is to create a Computer-Aided Diagnosis system that can automatically recognize the malaria status from blood smear images," Anto said in a discussion in Jakarta on Wednesday, May 7, 2025.
Anto explained that currently, malaria diagnosis is still done manually through a microscope. Depending only on the staff's skills, the process is prone to errors due to fatigue or limitations of expert personnel.
The data in this research were obtained from various endemic areas in Indonesia, such as Kalimantan, Papua, and Sumba. The PR-KAKS team collaborated with the Eijkman BRIN Center for Molecular Biology Research. The researchers analyzed 1,388 microphotographs, covering various types of Plasmodium, including P. falciparum, P. vivax, P. malariae, P. ovale, a case of mixed infection, and a negative sample.
"Based on the analysis of 35 micrographs from actual cases in endemic areas of Indonesia, covering 3,362 cells, this system has shown significant ability in identifying malaria parasites," Anto said.
The initial test showed a system sensitivity of 84.37 percent in differentiating healthy and infected cells, an accuracy (F1-score) of 80.60 percent, and a positive predictive value (PPV) of 77.14 percent.
The BRIN-made system is also designed to expedite mass blood surveys and enable remote diagnosis in remote areas. In endemic conditions, Anto continued, one blood smear may require the observation of 500-1,000 erythrocytes, or 200 leukocytes. "AI can expedite this process without sacrificing accuracy," he said.
Anto affirmed the importance of multidisciplinary collaboration in developing AI technology in the biomedical field. "We cannot solely rely on computational capabilities," he said. "Understanding the medical context is key to ensuring that the diagnostic results benefit patients."
The Major Threat of Malaria
Puji Budi Setia Asih, Principal Researcher at the Eijkman BRIN Center for Molecular Biology Research, mentioned that malaria remains a major health problem in Indonesia. A challenge in addressing this disease is the limitation of rapid and accurate diagnostic facilities at the primary care level.
"AI-based microscopic approaches will help improve diagnostic sensitivity and accuracy, which are prerequisites for malaria elimination," Puji said in a written statement.
She added that accurate diagnosis is crucial in determining treatment and further management. Smart intelligence is believed to help reduce malaria cases through early detection and timely treatment, especially in remote areas.
Another challenge is the lack of standardization in blood smear image staining. "BRIN is committed to continuously improving this system through collaborative research and field trials," Anto said.
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