Rate My Professor Friso De Boer

Professor Friso De Boer serves as a Professor in the College of Engineering, IT and Environment at Charles Darwin University, Darwin, Australia. He is a key member of the Biomedical Engineering and Health Informatics Research Group. De Boer's research focuses on the detection of abnormalities in biosignals using techniques such as time-frequency analysis, wavelet analysis, mathematical modelling, and artificial intelligence methods including machine learning and neural networks. Applications of his work encompass EEG signals for binaural hearing research, APG and ECG signals for heat stress detection, and AI for predicting breast cancer, cardiovascular disease, and kidney disease. His contributions extend to areas like image processing for medical diagnostics, including skin cancer detection, otitis media diagnosis, diabetic retinopathy, Alzheimer's disease classification, and respiratory diseases from lung ultrasound and X-rays.

Friso De Boer supervises PhD candidates on topics including quantification of binaural hearing via EEG signals and machine learning for disease detection and prediction. He has authored 82 publications, among them 'BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images' (2021), 'AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images' (2023), 'Reimagining Otitis Media Diagnosis: A Fusion of Nested U-Net Segmentation with Graph Theory-Inspired Feature Set' (2024), 'Automated Diagnosis of Respiratory Diseases from Lung Ultrasound Videos Ensuring XAI: An Innovative Hybrid Model Approach' (2024), 'ECgMLP: A novel gated MLP model for enhanced endometrial cancer diagnosis' (2025), 'Advancing skin cancer detection integrating a novel unsupervised classification and enhanced imaging techniques' (2025), and earlier papers such as 'Frequency bands effects on QRS detection' and 'Comparison of torque estimators for PMSM'. His work has accumulated over 2,700 citations, impacting biomedical signal processing, AI in healthcare, and mechatronics.