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Results for “"Michael A. Riegler"”

16+ results

Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

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Debesh Jha, Sharib Ali, Nikhil Kumar Tomar, Håvard D. Johansen et al.

Journal: IEEE AccessYear: 2021Citations: 388

Computer-aided detection, localisation, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of state-of-the-art methods still remains an open problem. This is due to the incr...

Health SciencesMedicineOncologyOpen Access
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[Invited papers] Comparing Approaches to Interactive Lifelog Search at the Lifelog Search Challenge (LSC2018)

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Cathal Gurrin, Klaus Schoeffmann, Hideo Joho, Andreas Leibetseder et al.

Journal: ITE Transactions on Media Technology and ApplicationsYear: 2019Citations: 80

The Lifelog Search Challenge (LSC) is an international content retrieval competition that evaluates search for personal lifelog data. At the LSC, content-based search is performed over a multi-modal dataset, continuously recorded by a lifelogger over 27 days, consisting of multimedia content, biomet...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Predicting an unstable tear film through artificial intelligence

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Fredrik Fineide, Andrea M. Storås, Xiangjun Chen, Morten Schjerven Magnø et al.

Journal: Scientific ReportsYear: 2022Citations: 22

Dry eye disease is one of the most common ophthalmological complaints and is defined by a loss of tear film homeostasis. Establishing a diagnosis can be time-consuming, resource demanding and unpleasant for the patient. In this pilot study, we retrospectively included clinical data from 431 patients...

Health SciencesMedicinePublic Health, Environmental and Occupational HealthOpen Access
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Using an AI-based avatar for interviewer training at Children’s Advocacy Centers: Proof of Concept

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Gunn Astrid Baugerud, Miriam S. Johnson, Rachel E. Dianiska, Ragnhild Klingenberg Røed et al.

Journal: Child MaltreatmentYear: 2024Citations: 14

= 68) took part in a virtual reality (VR) study in which they questioned an avatar presented as a child victim of sexual or physical abuse. Of interest was how interviewers questioned the avatar, how productive the child avatar was in response, and how interviewers perceived the VR interaction. Find...

Health SciencesMedicinePhysiologyOpen Access
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A field assessment of child abuse investigators' engagement with a child-avatar to develop interviewing skills

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Ragnhild Klingenberg Røed, Martine B. Powell, Michael A. Riegler, Gunn Astrid Baugerud

Journal: Child Abuse & NeglectYear: 2023Citations: 13

BACKGROUND: Child investigative interviewing is a complex skill requiring specialised training. A critical training element is practice. Simulations with digital avatars are cost-effective options for delivering training. This study of real-world data provides novel insights evaluating a large numbe...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Reflecting on LLM Support in Reflexive Thematic Analysis: An Exploratory Study

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Magnhild Vikan, Ramtin Aryan, Mari Serine Kannelønning, Michael Riegler et al.

Journal: Qualitative Health ResearchYear: 2025Citations: 7

The launch of ChatGPT in November 2022 accelerated discussions and research into whether base large language models (LLMs) could increase the efficiency of qualitative analysis phases or even replace qualitative researchers. Reflexive thematic analysis (RTA) is a commonly used method for qualitative...

Health SciencesMedicineHealth InformaticsOpen Access
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Foundation models: the next level of AI in ART

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Hugo L. Hammer, Vajira Thambawita, Michael A. Riegler

Journal: Human ReproductionYear: 2025Citations: 4

Artificial intelligence (AI) in ART has traditionally employed narrow, task-specific models for procedures such as embryo selection and sperm analysis. Although effective, these systems depend on extensive manual annotation and address isolated tasks rather than integrating the diverse data generate...

Health SciencesMedicinePublic Health, Environmental and Occupational HealthOpen Access
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Evaluating gradient-based explanation methods for neural network ECG analysis using heatmaps

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Andrea M. Storås, S. Maeland, Jonas L. Isaksen, Steven A. Hicks et al.

Journal: Journal of the American Medical Informatics AssociationYear: 2024Citations: 4

OBJECTIVE: Evaluate popular explanation methods using heatmap visualizations to explain the predictions of deep neural networks for electrocardiogram (ECG) analysis and provide recommendations for selection of explanations methods. MATERIALS AND METHODS: A residual deep neural network was trained on...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Exploring the clinical value of concept-based AI explanations in gastrointestinal disease detection

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Andrea M. Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin et al.

Journal: Scientific ReportsYear: 2025Citations: 3

Complex artificial intelligence models, like deep neural networks, have shown exceptional capabilities to detect early-stage polyps and tumors in the gastrointestinal tract. These technologies are already beginning to assist gastroenterologists in the endoscopy suite. To understand how these complex...

Health SciencesMedicineHealth InformaticsOpen Access
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ML-Peaks: CHIP-Seq Peak Detection Pipeline using Machine Learning Techniques

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Sajad Amouei Sheshkal, Michael A. Riegler, Hugo L. Hammer

Year: 2023Citations: 2

CHIP-Seq data is critical for identifying the locations where proteins bind to DNA, offering valuable insights into disease molecular mechanisms and potential therapeutic targets. However, identifying regions of protein binding, or peaks, in CHIP-seq data can be challenging due to limitations in pea...

Life SciencesBiochemistry, Genetics and Molecular BiologyMolecular BiologyOpen Access
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Impact of decoding strategies on GPU energy usage in large language model text generation

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Alireza Nik, Michael A. Riegler, Pål Halvorsen

Journal: Scientific ReportsYear: 2025Citations: 1

Decoding strategies significantly influence the quality and diversity of the generated text in Large Language Models (LLMs), yet their impact on computational resources, particularly GPU energy consumption, is insufficiently studied. This paper investigates the relationship between decoding techniqu...

Physical SciencesComputer ScienceInformation SystemsOpen Access
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It's All in the Game - an Exploration of Extensive Communication on Gaming Platforms and the Risks of Online Sexual Grooming

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Catharina Drejer, Saeed Shafiee Sabet, Gunn Astrid Baugerud, Michael A. Riegler

Journal: SSRN Electronic JournalYear: 2024Citations: 1
Social SciencesPsychologyClinical PsychologyOpen Access
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Development of Human Conjunctival Goblet Cell Segmentation Datasets to Improve Quantitation

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Fredrik Fineide, Jeffrey Bair, Tor Paaske Utheim, Michael A. Riegler et al.

Journal: Scientific DataYear: 2026

Dry eye disease is an inflammatory disease of the ocular surface and one of the most common pathologies in medicine. This multifactorial disease can cause significant morbidity and visual disturbance. The ocular tear film consists of an outer lipid layer, an underlying aqueous layer and an innermost...

Health SciencesMedicinePublic Health, Environmental and Occupational HealthOpen Access
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Investigating discrepancies in accuracy, agreement and interpretability for single-frame embryo classification tasks conducted by embryologists and deep learning models

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Radhika Kakulavarapu, Erwan Delbarre, Akriti Sharma, David Jahanlu et al.

Journal: Frontiers in Reproductive HealthYear: 2026

Introduction Artificial intelligence tools show promise in supporting clinical decision making, but their safe use requires evaluation of not only accuracy, but also agreement with experts and interpretability of model decisions. The aim of this study was to evaluate the accuracy and agreement of hu...

Health SciencesMedicinePublic Health, Environmental and Occupational HealthOpen Access
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Reply: Foundation models in IVF: from speculation to implementation with FEMI

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Hugo L. Hammer, Vajira Thambawita, Michael A. Riegler

Journal: Human ReproductionYear: 2025
Health SciencesMedicinePediatrics, Perinatology and Child Health
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