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30-Day Survival Probabilities as a Quality Indicator for Norwegian Hospitals: Data Management and Analysis

PloS one, 2015-09, Vol.10 (9), p.e0136547-e0136547

2015

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A Comparative Literature Review of Machine Learning and Image Processing Techniques Used for Scaling and Grading of Wood Logs

Forests, 2024-07, Vol.15 (7), p.1243

2024

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Statistical process control and interrupted time series: a golden opportunity for impact evaluation in quality improvement

BMJ quality & safety, 2015-12, Vol.24 (12), p.748-752

2015

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Statistics for sensory and consumer science

2nd Ed., 2010

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RENT-Repeated Elastic Net Technique for Feature Selection

IEEE access, 2021, Vol.9, p.152333-152346

2021

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Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Frontiers in medicine, 2023, Vol.10, p.1217037

2023

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Corrigendum: Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Frontiers in medicine, 2024-05, Vol.11, p.1421603-1421603

2024

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Characterization of Selected South African Young Cultivar Wines Using FTMIR Spectroscopy, Gas Chromatography, and Multivariate Data Analysis

Journal of agricultural and food chemistry, 2009-04, Vol.57 (7), p.2623-2632

2009

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Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning

Frontiers in veterinary science, 2023, Vol.10, p.1143986-1143986

2023

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Visualization of sensory profiling data for performance monitoring

Food science & technology, 2007-03, Vol.40 (2), p.262-269

2007

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Non-linear shrinking of linear model errors

Analytica chimica acta, 2023-06, Vol.1258, p.341147-341147, Article 341147

2023

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A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS)

Machine learning, 2022-10, Vol.111 (10), p.3897-3923

2022

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The effect of a biochar temperature series on denitrification: which biochar properties matter?

Soil biology & biochemistry, 2019-08, Vol.135, p.173-183

2019

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Temporal sweetness and side tastes profiles of 16 sweeteners using temporal check-all-that-apply (TCATA)

Food research international, 2019-07, Vol.121, p.39-47

2019

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Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

Computational materials science, 2022-02, Vol.202, p.110938, Article 110938

2022

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On the possible benefits of deep learning for spectral preprocessing

Journal of chemometrics, 2022-02, Vol.36 (2), p.n/a

2022

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Why use component-based methods in sensory science?

Food quality and preference, 2023-12, Vol.112, p.105028, Article 105028

2023

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Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

Computational materials science, 2021

2021

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Principal components analysis of descriptive sensory data: Reflections, challenges, and suggestions

Journal of sensory studies, 2021-10, Vol.36 (5), p.n/a

2021

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Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients

European journal of nuclear medicine and molecular imaging, 2021-08, Vol.48 (9), p.2782-2792

2021

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Sequential and orthogonalized PLS (SO‐PLS) regression for path analysis: Order of blocks and relations between effects

Journal of chemometrics, 2021-10, Vol.35 (10), p.n/a

2021

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Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival

Computer methods and programs in biomedicine, 2023

2023

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A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers

Physics in medicine & biology, 2021-03, Vol.66 (6), p.065012-065012

2021

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966: Uncertainty in deep learning-based automatic segmentations of head and neck cancer tumors

Radiotherapy and oncology, 2024-05, Vol.194, p.S3034-S3037

2024

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Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival

Computer methods and programs in biomedicine, 2024-02, Vol.244, p.107934-107934, Article 107934

2024

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30-Day Survival Probabilities as a Quality Indicator for Norwegian Hospitals: Data Management and Analysis

A Comparative Literature Review of Machine Learning and Image Processing Techniques Used for Scaling and Grading of Wood Logs

Statistical process control and interrupted time series: a golden opportunity for impact evaluation in quality improvement

Statistics for sensory and consumer science

RENT-Repeated Elastic Net Technique for Feature Selection

Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Corrigendum: Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Characterization of Selected South African Young Cultivar Wines Using FTMIR Spectroscopy, Gas Chromatography, and Multivariate Data Analysis

Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning

Visualization of sensory profiling data for performance monitoring

Non-linear shrinking of linear model errors

A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS)

The effect of a biochar temperature series on denitrification: which biochar properties matter?

Temporal sweetness and side tastes profiles of 16 sweeteners using temporal check-all-that-apply (TCATA)

Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

On the possible benefits of deep learning for spectral preprocessing

Why use component-based methods in sensory science?

Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

Principal components analysis of descriptive sensory data: Reflections, challenges, and suggestions

Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients

Sequential and orthogonalized PLS (SO‐PLS) regression for path analysis: Order of blocks and relations between effects

Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival

A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers

966: Uncertainty in deep learning-based automatic segmentations of head and neck cancer tumors

Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival

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