Automated system offers fast, reliable malaria screening
Parasite detection system uses machine learning to diagnose malaria from thin blood smears
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Luciana Stanica is a contributor to Physics World. She is a researcher in the Biosensing Department at the International Centre of Biodynamics in Romania. Her research concerns the development of a multi-parametric biosensing platform combining optical and electric techniques, more specifically total internal reflection fluorescence microscopy (TIRFM), surface plasmon resonance imaging (SPRi) and electrical impedance spectroscopy (EIS). These non-invasive label-free techniques are aimed to assay changes in cell dynamics upon exposure to chemical and physical stimuli towards cellular platforms development.
Her research activity during her Master's involved working with transfected oocytes that expressed TRPV1 channel and different pancreatic cell lines that expressed TRPM8 channel based on voltage and patch clamp technique.
Parasite detection system uses machine learning to diagnose malaria from thin blood smears
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