Disputas - Master of science Stig Uteng

Disputas - Stig Uteng

Master of science Stig Uteng will on August 19th at 12.15 publically defend his PhD degree in science.

Title of the PhD thesis:

"Statistical Curve Analysis: Developing Methods and Expanding Knowledge in Health"

Abstract

One of the main incentives for research is health. We have seen astonishing examples of health-driven research during the Covid 19 pandemic, with the incredibly fast development of vaccines. One of the main reasons for this development speed was the application of data science, where statistics play an integral part. In this dissertation, we will also apply statistics in health-related areas such as food quality, skin cancer, diabetes type 1 and liver transplantation.

Food quality is of high importance due to the severe consequences of contaminated or degraded food on human health. We have now developed a considerable amount of technology to prevent food spoilage. It will, however, always be interesting to monitor the degradation process. Due to this, we have developed a method for monitoring and detecting changes through the utilization of hyperspectral images.

Skin cancer is one of the most common forms of cancer, with more than 1.5 million new cases worldwide in 2020. Melanoma skin cancer accounts for about half of all skin cancer-related deaths. The 5-year survival rate is 99% when the cancer is detected early but drops to 25% once it becomes metastatic. In other words, the key to preventing death is early detection. We have developed a novel classification method which may be a valuable contribution to the important early phase of the treatment of malignant by exploiting some features in hyperspectral images.

Diabetes type 1 is a rather abundant disease, counting 53.7 million adults (20-79 years) as of 2021. There are several challenges for diabetes type 1 patients. For example, in physical activity, a drop in blood glucose can result in hypoglycemia for these patients and this poses a major fear. We have developed an improved method for estimating blood glucose so that diabetes type 1 patients can perform physical activity more safely.

Liver transplantation, also called hepatic transplantation, is the replacement of a non-functioning liver with a healthy liver from another person. This is a treatment option for end-stage liver disease and acute liver failure, although the availability of donor organs is a major limitation. When the liver is cut off from oxygenated blood several processes of degradation occur. Machine perfusion may reverse these degradation processes, and in addition, allow a performance assessment of the liver before transplantation. We investigate two different paths of machine perfusion and try to assess what method proves more suitable for the transplantation process.

The analysis of curves can be claimed to be the core of most scientific ventures. In this dissertation we have analyzed curves through the statistical lens of the two main methods, finding suitable critical decision regions and regression. These methods are very versatile techniques and have given successful solutions to the proposed problems from health-related fields presented here and will almost certainly be expanded and developed further in the future.

The thesis is published and available in Munin

Supervisors

•       Professor Fred Godtliebsen, IFT i 2008, UiT (main supervisor)
•       Professor Tor Arne Øigård, IFT i 2008, UiT  (co-supervisor)

Evaluation committee

•       Professor Jan Hannig, Statistics and Opperation Research, University of North Carolina, USA
(1. Opponent)
•       Dr. Maryam Tayefi, Nasjonal senter for e-helseforskning (NSE) Tromsø
(2. Opponent)
•       Førsteamanuensis Michael Kampffmeyen, IFT, UiT (intern member and leader of the commitee)

Leader of the defense: Professor Anders Andersen

Links to the trial lecture and defense will be possible to open when the live stream begins. If you haven`t clicked the link to the folder before it begins, refresh the web browser for them to become visible. If you have clicked the link to the trial lecture or defense before it has started, it will open automatically when the stream begins. 

Link to folder which contains trial lecture and defense

The trial lecture starts at 10.15 august 19th

Trial lecture

The defense starts at 12.15 august 19th

Defense

Når: 19. august 2022 kl. 12.15–16.00
Hvor: Teknobygget auditorium 1.022
Studiested: Digitalt, Tromsø
Målgruppe: Ansatte, Studenter, Gjester / eksterne
Kontakt: Eirik Derås Verlo
E-post: eve012@uit.no
Legg i kalender
Vedlegg / Bilder: