Oumayma Ben rhouma
About Me
I am Oumayma Ben Rhouma, a graduate of the Higher Institute of Medical Technology in Tunis with a master’s degree in embedded electronic systems and medical information processing.
Integrating your institution would be for me the opportunity to benefit from a quality environment and to acquire solid skills in my professional career. I aspire to find my first job as a data scientist. I already had a great experience as a data scientist at Tiamed Tunisia in a 6 months internship, this professional experience allowed me to face many challenges. First of all, I was able to identify relevant approaches based on ML as well as discover new approaches regarding unbalanced data. Second, I had the opportunity to analyze breast cancer data that included risk factors, as well as different search queries. Finally, I discovered how to build a web interface using “Streamlit” based on the risk estimation algorithm developed in Python.
Education
Higher Institute of Medical Technologies of Tunis (ISTMT)
Artificial Intelligence, Vision and Pattern Recognition, Medical Information Coding and Compression, Cloud Computing, Telemedicine, Enterprise Culture, Standards and Norms, Advanced Computing Architecture
Higher Institute of Medical Technologies of Tunis (ISTMT)
Network architectures and protocols, Linux operating system, Medical image processing, Electrophysiology, and biomedical signal processing, FPGA/VHDL digital design, Real-time systems, Data warehouse, English.
Higher Institute of Medical Technologies of Tunis (ISTMT)
Biophysics, Image networks, Signal processing, Image processing, Analog and digital electronics, Processor system architectures, Electrical engineering
Work & Experience
DATA SCIENTIST
Tiamed Tunisia
end of studies internship : Development of an algorithm that allows the estimation of risk of breast cancer within five years of the year of screening. Five asymmetric data balancing methods are proposed with eight classification models evaluated for best performance. Estimation of probabilities based on the best optimized classification model. Building a web interface using "Streamlit".
Biomedical Engineer
National Institute of Neurology of Tunis
Quantification of cerebral perfusion in MRI: application to the diagnosis of ischemic stroke in Matlab. The implementation of an algorithm allowing the extraction of cerebral hemodynamic parameters. Calculation and reconstruction of the quantitative parameter mapping "time to maximum (Tmax)". Estimation of hypoperfused volume.
