🦠 Malaria Diagnosis Enhanced with AI – Case Overview
Malaria remains a major public health challenge, particularly in low-income regions like Sub-Saharan Africa (SSA) and parts of Asia, which bear about 40% of the disease's global burden. In India, malaria continues to be a significant concern, with India accounting for 66% of malaria cases in the World Health Organization’s Southeast Asia region in 2022, according to the World Malaria Report(Frontiers).
However, India has made significant strides, achieving an 85% reduction in reported cases since 2015 after launching the National Framework for Malaria Elimination in 2016(World Health Organization (WHO)). Despite this progress, accurate diagnosis remains critical to ensure effective treatment and prevent transmission.
Malaria Diagnosis Methods:
The identification of malaria parasites or antigens in a host’s blood can be done through various methods, including microscopy, rapid diagnostic tests (RDTs), and polymerase chain reaction (PCR). Microscopy remains the gold standard for malaria diagnosis, allowing for the differentiation of the four key Plasmodium species: P. falciparum, P. vivax, P. ovale, and P. malariae. However, the use of microscopy requires skilled personnel, quality control, and proper equipment.
AI100 Powered by SHONIT
In response to these challenges, AI100 powered by SHONIT offers valuable assistance in the screening of malaria, especially with remote access capabilities. SHONIT flags malaria suspects with visual evidence, making the diagnostic process faster and more efficient. This is a game-changer, particularly in resource-limited settings where timely diagnosis is critical.
Case Example: Malaria Diagnosis with SHONIT
Presence of ring forms and banana boat-shaped gametocytes of P. falciparum in the peripheral blood smear, identified and flagged by SHONIT on AI100.
P. falciparum, the most virulent form of malaria, has the ability to remodel erythrocytes, leading to potentially life-threatening complications such as cerebral malaria and acute renal failure. Despite its deadly nature, there is research suggesting P. falciparum’s potential in cancer therapy, where its immune activation capabilities could be harnessed to target tumors(
World Health Organization (WHO)).
Early Diagnosis Saves Lives:
Early detection and diagnosis are critical to malaria control and elimination. AI100’s ability to provide early, precise detection allows for prompt treatment and effective surveillance, reducing the disease’s transmission potential. With AI tools like SHONIT, we are one step closer to making malaria history.
Case Courtesy: Dr Saumil Sanghavi, Sanghavi Lab, Mumbai
#Malaria #AIinHealthcare #SigTuple
Dr. Renu Ethirajan Dr Sharitha Naganna Dr Chaitra C Dr Pavithra Devi Dr Gayatri
