1. Presentation Slides
PhD Public Defence: Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things: Enhancing COVID-19 & Early Sepsis Detection
2. Demo App
Paper: SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction, Codes & Results
3. Presentation Slides
Paper: COVID-19 detection from thermal image and tabular medical data utilizing multi-modal machine learning, Codes & Results
4. Presentation Slides
Paper: FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices, Codes
5. Presentation Video
Paper: Exploring LRP and Grad-CAM visualization to interpret multi-label-multi-class pathology prediction using chest radiography, Best Student Paper Award, Codes & Results
6. Poster Presentation
7. Presentation Slides
8. Presentation Video
Paper: Intelligent context-based healthcare metadata aggregator in internet of medical things platform
9. Presentation Video
Paper: Deep Learning from Heterogeneous Sequences of Sparse Medical Data for Early Prediction of Sepsis, Best Paper Award
10. Presentation Slides
Master’s Thesis: From speech to image; a novel approach to understand the hidden layer mechanisms of deep neural networks in automatic speech recognition.
