Talked about Machine Learning in Digital Medicine

Dr. Giorgio Quer in USN auditorium speaking to students and researchers in Kongsberg. Photo
Dr. Giorgio Quer in the USN auditorium speaking to students and researchers in Kongsberg. Photo: Hứa Minh Tuấn

Department of Science and Industry Systems had the pleasure to organise an IEEE Distinguished Lecture on Machine Learning in Digital Medicine, at campus Kongsberg.

Dr. Giorgio Quer is a Sr. Research Scientist at the Scripps Research (SR) in San Diego, California, and the Director of Artificial Intelligence at the SR Translational Institute.

His key points at the lecture:

‹Digitalise human beings using biosensors to track our complex physiologic system, process the large amount of data generated with artificial intelligence (AI) and change clinical practice towards individualised medicine: these are the goals of digital medicine.

At Scripps, we are a team of computer scientists, engineers, and clinical researchers, in partnership with health industries, and we propose new solutions to analyse large longitudinal data using statistical learning and deep convolutional neural networks to address different cardiovascular health issues.

One of the greatest contributors to premature mortality worldwide is hypertension. Lowering blood pressure (BP) by just a few mmHg can bring substantial clinical benefits, but it is hard to assess the “true” BP for an individual, since it fluctuates significantly.

With a dataset of 16 million BP measurements, we unveil the BP patterns and provide insights on the clinical relevance of these changes.

Another prevalent health issue is atrial fibrillation (AF), the most common sustained cardiac arrhythmia, associated with stroke, heart failure and coronary artery disease.

AF detection from single-lead electrocardiography (ECG) recordings is still an open problem, as AF events may be episodic and the signal noisy.

We conduct a thoughtful analysis of recent convolutional neural network architectures developed in the computer vision field, redesigned to be suitable for a one-dimensional signal, and we evaluate their performance in the detection of AF using 200 thousand seconds of ECG, highlighting the potential and pitfall of this technology.

Looking to the future, we investigate new applications for wearable devices and advanced processing in the All of Us Research Program, an unprecedented research effort to gather data from one million people in the USA to accelerate the advent of precision medicine.›

Dr. Giorgio Quer, front row, fourth from left, together with engineering-students, researchers and staff at USN Kongsberg. Photo: Hứa Minh Tuấn

Dr. Giorgio Quer

  • He received the B.Sc. degree, the M.Sc. degree (with honors) in Telecommunications Engineering and the Ph.D. degree (2011) in Information Engineering from University of Padova, Italy.
  • In 2007, he was a visiting researcher at the Centre for Wireless Communication at the University of Oulu, Finland.
  • During his Ph.D., he proposed a solution for the distributed compression of wireless sensor networks signals, based on the joint exploitation of Compressive Sensing and Principal Component Analysis.
  • From 2010 to 2017, he was a visiting scholar at the California Institute for Telecommunications and Information Technology and then a postdoc at the Qualcomm Institute, University of California San Diego (UCSD), working on cognitive networks protocols and implementation.
  • He is a Senior Member of the IEEE, a member of the American Heart Association (AHA), and a Distinguished Lecturer for the IEEE Communications society. His research interests include wireless sensor networks, compressive sensing, probabilistic models, deep convolutional networks, wearable sensors, physiological signal processing, and digital medicine.



The lecture was organised by Associate Professor Filippo Sanfilippo, who is the Membership Development Officer for the IEEE Norway Section. He is also the treasurer of the IEEE Robotics and Automation, Control Systems and Intelligent Transportation Systems Joint Chapter. Sanfilippo is also the treasurer of the Norsk Forening for Kunstig Intelligens (NAIS), the Norwegian Association for Artificial Intelligence.

IEEE and Tekna:

The Institute of Electrical and Electronics Engineers (IEEE) is the world's largest technical professional organisation dedicated to advancing technology for the benefit of humanity. The IEEE Distinguished Lecture program provides lectures worldwide to present topics of current interest. The lecturers are well-known experts who have been working in the selected areas for long time.
The event was also supported by Tekna, the Norwegian society of graduate technical and scientific professionals.

Outcome and benefits:

  • This IEEE Distinguished Lecture is part of a long-term strategy for the department to promote research activities and establish international cooperations with well-established research teams, both at the national level as well as internationally.
  • The topic of health technology is seen as a strategic research field for USN by Associate Professor Filippo Sanfilippo, who is also working on developing novel assistive health systems.
  • This IEEE Distinguished Lecture is also part of a series of seminars that will be periodically presented at the department.
  • This series of seminars is instrumental for involving active researchers and also students in an active education/research loop. Associate Professor Filippo Sanfilippo is also working towards the establishment of an IEEE student branch at USN. All the interested students are invited to join the branch.