Gaetano Scebba
Gaetano Scebba
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I presented our work on Large Language Models at BioTechX conference (October 2023)
I held a tutorial on Foundations of ML for health data at Google Health GenAI hackathon (September 2023)
Our analysis on motor-cognitive dual tasking in Alzheimer's disease has been presented at the Alzheimer's Association International Conference (July 2023)
Our patent application "A system for recording a high-quality wound image and for real-time image quality assessment" was published at the European Patent Office (November 2022)
I have joined Novartis as Data Scientist in Translational Medicine (July 2022)
Our paper "Detect-and-Segment: a deep learning approach to automate wound image segmentation" has been accepted to Informatics in Medicine Unlocked (February 2022)
We released a new preprint on robust wound image segmentation with deep neural networks (November 2021)
Our paper 'Wound Image Quality From a Mobile Health Tool for Home-Based Chronic Wound Management With Real-Time Quality Feedback Randomized Feasibility Study' has been accepted to JMIR mHealth. (July 2021)
I successfully defended my PhD thesis "Robust Health Monitoring with Digital Cameras" at ETH Zurich, Switzerland. (April 2021)
Our paper 'Multispectral Video Fusion for Non-contact Monitoring of Respiratory Rate and Apnea' has been accepted to the IEEE TBME Journal (May 2020)
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