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A novel 'man and machine' decision support system makes malaria diagnostics more effective
Date:8/21/2014

ries. In the next phase of our project we will test the system in combination with inexpensive mobile microscopy devices that our group has also developed", told the shared first author of the article Nina Linder (MD, PhD) from FIMM.

The developed support system can be applied in various other fields of medicine. In addition to other infectious diseases such as tuberculosis, the research group is planning to test the system fro cancer diagnostics in tissue samples.

"There is also a strong need for fast and accurate methods for measuring the malaria parasite load in a sample. Various malaria drug screening programs are underway and the parasite load in a large number of samples needs to be quantified for determining the efficacy of potential drugs. We are further developing the computer algorithms used in this study to meet this need as well", Dr. Linder continued.

There are more than 200 million new malaria cases yearly. High-quality microscopy is still the most accurate method for detection of malaria infection. However, microscopy requires well-trained personnel and can be very time-consuming when performed according to the recommendations. In 2012, less than half of the suspected malaria cases in Sub-Saharan Africa received a diagnostic test. The workload of the health-care personnel is excessive thus contributing to the demonstrably low accuracy of microscopy.

"The new method of imaging and analysis can revolutionise the point of care diagnostics of not only malaria but also several diseases where diagnosis depends on microscopy. The action may lead to 'market rupture' in the field of disease diagnostics", says Professor Vinod Diwan from Karolinska Institutet.


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Contact: Dr. Nina Linder
nina.linder@helsinki.fi
358-445-555-407
University of Helsinki
Source:Eurekalert  

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A novel 'man and machine' decision support system makes malaria diagnostics more effective
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