17th Presentation | Classification of hemoglobin fractions in the liquid state using Raman spectroscopy combined with machine learning | Mehdi ‘Arash’ Feizpour
You can watch presentation’s recording here!
NanoAI welcomes Mehdi ‘Arash’ Feizpour who will present his work, titled “Classification of hemoglobin fractions in the liquid state using Raman spectroscopy combined with machine learning”.
As always, an open discussion will follow.
When? November 9th, 15:00 Greece
Description:
Detecting hemoglobinopathies is crucial for the effective clinical management of various diseases, including diabetes. A common method for screening these conditions involves high-performance liquid chromatography separation with subsequent UV-VIS detection. Although UV–VIS can quantify the hemoglobin fractions, it is unable to identify them. In this context, we demonstrate how Raman microscopy can be used to create distinctive spectral fingerprints of different hemoglobin fractions, enabling their precise identification. Five different hemoglobin types are investigated in their liquid state: HbA0, HbS, HbF, HbA1c, and HbA2. Machine learning models including a support vector machine and multilayer perceptron are optimized via a genetic algorithm to classify these fractions.
Mehdi ‘Arash’ Feizpour is a PhD candidate in the field of nanobiophotonics at the Brussels Photonics Team of Vrije Universiteit Brussel. His research is focused on the development of spectroscopic medical diagnostic tools based on optofluidics, biochemistry, and machine learning with which he tries to feed his insatiable appetite for challenges.
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