Blar i Fakultet for informasjonsteknologi og elektroteknikk (IE) på forfatter "Bach, Kerstin"
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Creating Explainable Dynamic Checklists via Machine Learning to Ensure Decent Working Environment for All: A Field Study with Labour Inspections
Flogard, Eirik Lund; Mengshoel, Ole Jakob; Theisen, Ole Magnus; Bach, Kerstin (Chapter, 2023)To address poor working conditions and promote United Nations’ sustainable development goal 8.8, “protect labour rights and promote safe working environments for all workers [...]”, government agencies around the world ... -
Data Analysis for the Mobile Application of the selfBACK Decision Support System
He, Yu (Master thesis, 2018)The aim of the thesis is to find user behavior patterns by applying unsupervised learning methods on the selfBACK app usage data. The recognized patterns will be used as references to select interviewees in the process ... -
Data Analytics for HUNT: Recognition of Physical Activity on Sensor Data Streams
Reinsve, Øyvind (Master thesis, 2018)Human Activity Recognition (HAR) is the field of recognizing activities by analyzing measurements of a subject s movement and environment. A major application of HAR systems is medical research. Th e Nord-Trøndelag Health ... -
A Data-Driven Approach for Determining Weights in Global Similarity Functions
Jaiswal, Amar Deep; Bach, Kerstin (Peer reviewed; Journal article, 2019)This paper presents a method to discover initial global similarity weights while developing a case-based reasoning (CBR) system. The approach is based on multiple feature relevance scoring methods and the relevance of ... -
Decision support in patient-centered health care
Prestmo, Tale (Master thesis, 2017)This thesis aims to create exercise plans for patients with low back pain and is a part of the research project selfBACK. Case-based reasoning is used to create the exercise plans, which is the process of solving new ... -
Deep Learning for Blind Calibration of Wireless Sensor Networks
Ljunggren, Erling (Master thesis, 2020)Temporal drift of low-cost sensors is a crucial problem when considering the applicability of wireless sensor networks (WSN). Since they provide highly local measurements, which is key to combat the ever increasing problem ... -
Design of a clinician dashboard to facilitate co-decision making in the management of non-specific low back pain
Bach, Kerstin; Marling, Cindy; Mork, Paul Jarle; Aamodt, Agnar; Mair, Frances; Nicholl, Barbara I (Journal article; Peer reviewed, 2018)This paper presents the design of a Clinician Dashboard to promote co-decision making between patients and clinicians. Targeted patients are those with non-specific low back pain, a leading cause of discomfort, disability ... -
Detecting and Localizing Cell Nuclei in Medical Images.
Loudon, Johan Scott (Master thesis, 2018)In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and localizing nuclei in medical imaging. Mask R-CNN, which does instance segmentation, was chosen as the architecture to implement, ... -
A digital decision support system (selfBACK) for improved self-management of low back pain: a pilot study with 6-week follow-up
Sandal, Louise Fleng; Øverås, Cecilie K.; Nordstoga, Anne Lovise; Wood, Karen; Bach, Kerstin; Hartvigsen, Jan; Søgaard, Karen; Mork, Paul Jarle (Peer reviewed; Journal article, 2020)Background Very few of the publicly available apps directed towards self-management of low back pain (LBP) have been rigorously tested and their theoretical underpinnings seldom described. The selfBACK app was developed ... -
Effect of an Artificial Intelligence-Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial
Marcuzzi, Anna; Nordstoga, Anne Lovise; Bach, Kerstin; Aasdahl, Lene; Nilsen, Tom Ivar Lund; Bardal, Ellen Marie; Boldermo, Nora; Bertheussen, Gro Falkener; Marchand, Gunn Hege; Gismervik, Sigmund Østgård; Mork, Paul Jarle (Peer reviewed; Journal article, 2023)Importance Self-management is a key element in the care of persistent neck and low back pain. Individually tailored self-management support delivered via a smartphone app in a specialist care setting has not been ... -
Effectiveness of App-Delivered, Tailored Self-management Support for Adults With Lower Back Pain–Related Disability A selfBACK Randomized Clinical Trial
Fleng Sandal, Louise; Bach, Kerstin; Øverås, Cecilie K.; Jagd Svendsen, Malene; Dalager, Tina; Stejnicher Drongstrup Jensen, Jesper; Kongsvold, Atle Austnes; Nordstoga, Anne Lovise; Bardal, Ellen Marie; Ashikhmin, Ilya; Wood, Karen; Rasmussen, Charlotte Diana Nørregaard; Stochkendahl, Mette J; Nicholl, Barbara I; Wiratunga, Nirmalie; Cooper, Kay; Hartvigsen, Jan; Kjaer, Per; Sjøgaard, Gisela; Nilsen, Tom Ivar Lund; Mair, Frances S; Søgaard, Karen; Mork, Paul Jarle (Journal article; Peer reviewed, 2021) -
Ensemble Classifier Managing Uncertainty in Accelerometer Data within Human Activity Recognition Systems
Wold, Thomas; Skaugvoll, Sigve André Evensen (Master thesis, 2019)Human activity recognition (HAR) er et forskningsområde med mål om å klassifisere aktiviteter utført av personer ved hjelp av data hentet inn av video eller sensorer festet på kroppen. HUNT er den største helseundersøkelsen ... -
Ensemble Classifier Managing Uncertainty in Accelerometer Data within Human Activity Recognition Systems
Wold, Thomas; Skaugvoll, Sigve André Evensen (Master thesis, 2019)Human activity recognition (HAR) er et forskningsområde med mål om å klassifisere aktiviteter utført av personer ved hjelp av data hentet inn av video eller sensorer festet på kroppen. HUNT er den største helseundersøkelsen ... -
Explaining CBR Systems Through Retrieval and Similarity Measure Visualizations: A Case Study
Marin Veites, Paola; Bach, Kerstin (Chapter, 2022)Explainability in AI is becoming increasingly important as we delegate more safety-critical tasks to intelligent decision support systems. Case-Based Reasoning (CBR) systems are one way to build such systems. Understanding ... -
Explaining your Neighbourhood: A CBR Approach for Explaining Black-Box Models
Bayrak, Betül; Marin Veites, Paola; Bach, Kerstin (Peer reviewed; Journal article, 2022) -
Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes
Verma, Deepika; Jansen, Duncan; Bach, Kerstin; Poel, Mannes; Mork, Paul Jarle; Oude Nijeweme d’Hollosy, Wendy (Peer reviewed; Journal article, 2022)Background Patient-reported outcome measurements (PROMs) are commonly used in clinical practice to support clinical decision making. However, few studies have investigated machine learning methods for predicting PROMs ... -
FishNet: A Unified Embedding For Salmon Recognition
Meidell, Espen; Sjøblom, Edvard Schreiner (Master thesis, 2019)Dagens metoder for markering og sporing av oppdrettslaks baserer seg p˚a fysisk kontakt med fisken. Denne prosessen er b˚ade ineffektiv, stressende og potensielt skadelig for laksen. Bruken av dyp læring har de siste ˚arene ... -
FishNet: A Unified Embedding for Salmon Recognition
Meidell, Espen; Sjøblom, Edvard Schreiner (Master thesis, 2019)Dagens metoder for markering og sporing av oppdrettslaks baserer seg på fysisk kontakt med fisken. Denne prosessen er både ineffektiv, stressende og potensielt skadelig for laksen. Bruken av dyp læring har de siste årene ... -
FishNet: A Unified Embedding for Salmon Recognition
Mathisen, Bjørn Magnus; Bach, Kerstin; Meidell, Espen; Måløy, Håkon; Sjøblom, Edvard Schreiner (Chapter, 2020)Identifying individual salmon can be very beneficial for the aquaculture industry as it enables monitoring and analyzing fish behavior and welfare. For aquaculture researchers identifying indi- vidual salmon is imperative ... -
From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development
Veiga, Tiago Santos; Munch-Ellingsen, Arne; Papastergiopoulos, Christoforos; Tzovaras, Dimitrios; Kalamaras, Ilias; Bach, Kerstin; Votis, Konstantinos; Akselsen, Sigmund (Peer reviewed; Journal article, 2021)Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and ...