This is an overview of my publications. I have sorted them under the following categories (see below):
- Books
- Doctor scientarium thesis
- Peer-reviewed articles in scientific journals
- Peer-reviewed conference proceedings
- Reports on health services in Norway
- Popular science articles
- Conference posters
In each category, the newest publications are at the top and the oldest at the bottom.
BOOKS
Statistics for Sensory and Consumer Science, Tormod Næs, Per Bruun Brockhoff, Oliver Tomic, Wiley & Sons, 2010, ISBN: 978-0-470-51821-2 [more]
DOCTOR SCIENTARIUM THESIS
Computational methods for improved applicability of gas-sensor array technology, June 2004, Oliver Tomic, Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences (former Agricultural University of Norway), Ås, Norway [more]
PEER-REVIEWED ARTICLES IN SCIENTIFIC JOURNALS
(45) A. Jenul, H.L. Stokmo, S. Schrunner, G.O. Hjortland, M.-E. Revheim, O. Tomic, Novel Ensemble Feature Selection Techniques Applied to High-GradeGastroenteropancreatic Neuroendocrine Neoplasms for the Prediction of Survival. Computer Methods and Programs in Biomedicine, 244 (2024) [more]
(44) T. Næs, P. Varela, J.C. Castura, R. Bro, O. Tomic, Why use component-based methods in sensory science? Food Quality and Preference, 112 (2023) [more]
(43) B.N. Huynh, A.R. Grøndahl, O. Tomic, K.H. Liland, I.S. Knudtsen, F. Hoebers, W. van Elmpt, E. Malinen, E. Dale, C.M. Futsæther. Head and neck cancer treatment outcome prediction: A comparison between machine learning with conventional radiomics features and deep learning radiomics. Frontiers in Medicine, 10 (2023) [more]
(42) L. Fongaro, C. Futsæther, O. Tomic, I.B. Lande, K. Kvaal, M. Wallenius, K. Mayer, Development of a new approach for rapid identification and classification of uranium ore concentrate powders using textural and spectroscopy signatures, Chemometrics and Intelligent Laboratory Systems, 239 (2023) 104858 [more]
(41) R. Helin, U.G. Indahl, O. Tomic, K.H. Liland. Non-Linear Shrinking of Linear Model Errors. Analytica Chimica Acta, 1258 (2023) [more]
(40) A.R. Grøndahl, B.N. Huynh, O. Tomic, Åste Søvik, E. Dale, E. Malinen, H.K. Skogmo, C.M. Futsæther. Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning. Frontiers in Veterinary Science, 10 (2023) [more]
(39) A. Jenul, S. Schrunner, J. Pilz, O. Tomic. A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS). Machine Learning, 11 (2022), Springer. [more]
(38) A.R. Grøndahl, Y.M. Moe, C.K. Kaushal, B.N. Huynh, E. Rusten, O. Tomic, E. Hernes, B. Hanekamp, C. Undseth, M.G. Guren, E. Malinen, C.M. Futsæther. Deep learning-based automatic delineation of anal cancer gross tumor volume: A multimodality comparison of CT, PET and MRI. Acta Oncologica, 61 (2022). [more]
(37) A. Jenul, S. Schrunner, K.H. Liland, U.G. Indahl, C.M. Futsæther, O. Tomic. RENT – Repeated Elastic Net Technique for Feature Selection. IEEE Access, 9 (2021). [more]
(36) R. Tranås, O.M. Løvvik, O. Tomic, K. Berland. 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). [more]
(35) R. Helin, U.G. Indahl, O. Tomic, K.H. Liland. On the possible benefits of deep learning for spectral pre-processing. Journal of Chemometrics, (2021). [more]
(34) A. Jenul, S. Schrunner, B.N. Huynh, O. Tomic. RENT – A Python Package for Repeated Elastic Net Feature Selection. Journal of Open Source Software. 6 (2021). [more]
(33) T. Næs, O. Tomic, I. Endrizzi, P. Varela. Principal components analysis of descriptive sensory data: reflections, challenges and suggestions. Journal of Sensory Studies, (2021) [more]
(32) A. Rossvoll Grøndahl, I. Skjei Knudtsen, B. Ngoc Huynh, M. Mulstad, Y. Mardal Moe, F. Knuth, O. Tomic, U.G. Indahl, T. Torheim, E. Dale, E. Malinen, C.M. Futsæther, A comparison of fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers, Physics in Medicine and Biology (2021) [more]
(31) Y.M. Moe, A. Rossvoll Grøndahl, O. Tomic, E. Dale, E. Malinen, C.M. Futsæther, Deep learning-based auto-delineation of gross tumour volumesand involved nodes in PET/CT images of head and neck cancer patients, European Journal of Nuclear Medicine and Molecular Imaging, 48 (2021), 2782–2792 [more]
(30) J. Niimi, K.H. Liland, O. Tomic, D.W. Jeffery, S.E.P. Bastian, P.K. Boss, Prediction of wine sensory properties and using mid-infrared spectra of Cabernet Sauvignon and Chardonnay grape berries and wines, Food Chemistry (2021), 344 [more]
(29) T. Næs, R. Romano, O. Tomic, I. Måge, A. Smilde, K.H. Liland, Sequential and orthogonalized PLS (SO-PLS) regression for path analysis: Order of blocks and relations between effects, Journal of Chemometrics, 35 (2020) [more]
(28) Q.C. Nguyen, K.H. Liland, O. Tomic, A. Tarrega, P. Varela, T. Næs, SO-PLS as an alternative approach for handling multi-dimensionality in modelling different aspects of consumer expectations, Food Research International, 133 (2020) [more]
(27) J. Niimi, O. Tomic, T. Næs, S.E.P. Bastian, D.W. Jeffery, E.L. Nicholson, S.M. Maffei, P.K. Boss, Objective measures of grape quality: From Cabernet Sauvignon grape composition to wine sensory characteristics, LWT, 123 (2020) [more]
(26) V. Tan, M.W.S. May, O. Tomic, C.G. Forde, Rate‐All‐That‐Apply (RATA) comparison of taste profiles for different sweeteners in black tea, chocolate milk, and natural yogurt, Journal of Food Science, 85 (2020), 486-492 [more]
(25) O. Tomic, T. Graff, K. H. Liland, T. Næs, hoggorm: a python library for explorative multivariate statistics, Journal of Open Source Software, 4 (2019), 980 [more]
(24) S. Weldon, D.P. Rasse, A. Budai, O. Tomic, P. Dörsch, Biochar and denitrification: Examining the effect of a biochar temperature series on the kinetics of gaseous N turnover. Which properties matter?, Soil Biology and Biochemistry, 135, (2019) 173-183 [more]
(23) V. Tan, M.W.S. Mei, O. Tomic, C.G. Forde , Temporal sweetness and side tastes profiles of 16 sweeteners using temporal check-all-that-apply (TCATA), Food Research International, 121 (2019) 39-47 [more]
(22) J. Helgeland, O. Tomic, T.M. Hansen, D.T. Kristoffersen, S. Hassani, A.K. Lindahl, Postoperative wound dehiscence after laparatomy: A useful health quality indicator? A cohort study based on Norwegian hospital administrative data. BMJ Open, 9 (2019) [more]
(21) R. Romano, O. Tomic, K.H. Liland, A. Smilde, T. Næs, A comparison of two PLS based approaches to Structural Equation Modeling, Journal of Chemometrics, 33 (2019) [more]
(20) J. Niimi, O. Tomic, T. Næs, D.W. Jeffery, S.E.P. Bastian, P.K. Boss, Application of sequential and orthogonalised-partial least squares (SO-PLS) regression to predict sensory properties of Cabernet Sauvignon wines from grape chemical composition, Food Chemistry, 256 (2018), 195-202 [more]
(19) S. Hassani, A.S. Lindman, D.T. Kristoffersen, O. Tomic, J. Helgeland, 30-Day survival probabilities as a quality indicator for Norwegian hospitals: data management and analysis, PLOS ONE, 10 (2015) [more]
(18) A. Fretheim, O. Tomic, Statistical Process Control and Interrupted Time Series: A golden opportunity for impact evaluation in quality improvement, BMJ Quality and Safety, (2015) [more]
(17) M. Rødbotten, O. Tomic, A.K. Holtekjølen, I.S. Grini, P. Lea, B.S. Granli, S. Grimsby, S. Sahlström, Barley bread with normal and low content of salt: sensory profile and consumer preference in five European countries, Journal of Cereal Science 64 (2015), 176 – 182 [more]
(16) O. Tomic, I. Berget, T. Næs, A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data, Food Quality and Preference 43 (2015) 34-46 [more]
(15) E. Menichelli, T. Almøy, O. Tomic, T. Næs, SO-PLS as an exploratory tool for path modelling, Food Quality and Preference 36 (2014), 122–134 [more]
(14) T. Næs, O. Tomic, K. Greiff, K. Thyholt, A comparison of methods for analyzing multivariate sensory data in designed experiments – a case study of salt reduction in liver paste, Food Quality and Preference 33 (2014), 64-73 [more]
(13) T. Næs, O. Tomic, N.K. Afseth, V. Segtnan, I. Måge, Multi-block regression based on combinations of orthogonalisation, PLS-regression and canonical correlation analysis, Chemometrics and Intelligent Laboratory Systems 124 (2013), 32-42 [more]
(12) O. Tomic, C. Forde, C. Delahunty, T. Næs, Performance indices in descriptive sensory analysis – a complimentary screening tool for assessor and panel performance, Food Quality and Preference 28 (2013), 122-133 [more]
(11) T. Næs, O. Tomic, Mevik, B.-H., Martens, H., Path modeling by sequential PLS regression, Journal of Chemometrics 25 (2011), 28-40 [more]
(10) O. Tomic, G. Luciano, A. Nilsen, G. Hyldig, K. Lorensen, T. Næs, Analysing sensory panel performance in a proficiency test using the PanelCheck software, European Food Research and Technology 230 (2010), 497-511 [more]
(09) L. Louw, K. Roux, A. Tredoux, O. Tomic, T. Næs, H.H. Nieuwoudt, P. van Rensburg, Characterisation of selected South African young cultivar wines using FTMIR spectroscopy, gas chromatography and multivariate data analysis, The Journal of Agriculture and Food Chemistry 58 (2009), 2623-2632 [more]
(08) T. Dahl, O. Tomic, J.P. Wold, T. Næs, Some new tools for visualising multi-way sensory data, Food Quality and Preference 19/1 (2008), 103-113 [more]
(07) R. Romano, P.B. Brockhoff, M. Hersleth, O. Tomic, T. Næs, Correcting for different use of the scale and the need for further analysis of individual differences in sensory analysis, Food Quality and Preference 19/2 (2008), 197-209 [more]
(06) O. Tomic, A. Nilsen, M. Martens, T. Næs, Visualization of sensory profiling data for performance monitoring, LWT 40 (2007), 262-269 [more]
(05 ) E. Olsen, A. Veberg, G. Vogt, O. Tomic, B. Kirkhus, D. Ekeberg, A. Nilsson, Analysis of early lipid oxidation in salmon patè with cod liver oil and antioxidants, Journal of Food Science vol. 71, no. 3, (2006), 284-292 [more]
(04) O. Tomic, T. Eklöv, K. Kvaal, J.E. Haugen, Recalibration of gas-sensor array system related to sensor replacement, Analytica Chimica Acta 512 (2004), 199-206 [more]
(03) M. Kermit, O. Tomic, Independent component analysis applied on gas sensor array measurement data, IEEE Sensors Journal, 3/2 (2003), 218-228 [more]
(02) O. Tomic, H. Ulmer, J.E. Haugen, Standardization methods for handling instrument related signal shift in gas-sensor array measurement data, Analytica Chimica Acta 472 (2002), 99-111 [more]
(01) J.E. Haugen, O. Tomic, K. Kvaal, A calibration method for handling the temporal drift of solid state gas-sensors, Analytica Chimica Acta 407 (2000), 23-39 [more]
PEER-REVIEWED CONFERENCE PAPERS
(11) K.H. Liland, O. Tomic, U.G. Indahl, C.M. Futsæther, L. Jiao, O.-C. Granmo, L.G. Snipen. Tsetlin Machine in DNA sequence classification. ISTM2023 – Second International Symposium on the Tsetlin Machine, (2023). Accepted June 2023 at IEEE
(10) A. Jenul, S. Schrunner, B.N. Hyunh, R. Helin, C.M. Futsæther, K.H. Liland, O. Tomic. Ranking feature-block importance in artificial multiblock neural networks. 31st International Conference on Artificial Neural Networks – ICANN 2022, (2022). [more]
(09) A. Jenul, B. Bhattarai, K.H. Liland, L. Jiao, S. Schrunner, C.M. Futsæther, O.-C. Granmo, O. Tomic. Component based pre-filtering of noisy data for improved Tsetlin machine modelling. ISTM2022 – First International Symposium on the Tsetlin Machine, (2022). [more]
(08) B.N. Huynh, J. Ren, A.R. Grøndahl, O. Tomic, S.S. Korreman, C.M. Futsæther. Comparing deep learning and conventional machine learning for outcome prediction of head and neck cancer in PET/CT. MICCAI2021 – 24th Conference on Medical Image Computing & Computer Assisted Intervention, HECKTOR2021, (2021) [more]
(07) J. Ren, B.N. Huynh, A.R. Grøndahl, O. Tomic, C.M. Futsæther, S.S. Korreman. PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT. MICCAI2021 – 24th Conference on Medical Image Computing & Computer Assisted Intervention, HECKTOR2021, (2021) [more]
(06) A. Borowiak, U. Reiter, O. Tomic, Measuring the Quality of Long Duration AV Content – Analysis of Test Subject / Time Interval Dependencies, 10th European Interactive TV Conference: Bridging People, Places and Platforms, QoEMCS 2012 workshop (2012), 266-269 [more]
(05) O. Tomic, J.P. Wold, Rapid analysis and information fusion for quantification of intramuscular fat content, Proc. The Sixth International Conference on Information Fusion, 8-11 July 2003, Cairns, Australia, pp 358-364. ISBN 0-9721844-3-0 [more]
(04) O. Tomic, M. Kermit, Discrimination and interpretation of electronic nose data using ICA. In Lee, Jung, Makeig and Sejnowski (editors): 3rd International Conference on Independent Component Analysis and Blind Signals Separation (ICA 2001), 429-432, San Diego, CA, USA, December 9 – 12, 2001
(03) M. Kermit, O. Tomic, Independent components of odour signals, In Lee, Jung, Makeig and Sejnowski (editors): 3rd International Conference on Independent Component Analysis and Blind Signals Separation (ICA 2001), 355 – 360, San Diego, CA, USA, December 9 – 12, 2001
(02) M. Kermit, O. Tomic, Increased discrimination between odor signals by independent component analysis, Proc. Artificial intelligent and soft computing, 21-24 May 2001, Cancun, Mexico, pp 354-358. ISBN 0-88986-283-4.
(01) J.-E. Haugen, O. Tomic, F. Lundby, K. Kvaal, E. Strand, L. Svela, K. Jørgensen, Analysis of off-flavours in raw cow’s milk with a commercial gas-sensor system. In: Electronic Noses and Olfaction 2000., (Eds. J.W. Gardner & K.C. Persud), IoP London, England pp 265-271, ISBN 0750307641. [more]
PAPERS ON arxiv.org
(1) O. Tomic, A. Kuznetsova, P.B. Brockhoff, T. Graff, T. Næs. ConsumerCheck – A Software for Analysis of Sensory and Consumer Data (2022) [more]
REPORTS ON HEALTH SERVICES IN NORWAY
(14) Hansen TM, Saunes IS, Tomic O, Lindahl A.K. Helse i Norge 2017 – Kommentarrapport til OECDs sammenligning av helse i ulike land. ISBN: 978-82-8082-883-5. (English title: Health in Norway 2017 – commentary report on OECD comparison of various countries). (2017)
(13) Hansen TM, Kristoffersen DT, Tomic O, Helgeland J. Kvalitetsindikatoren 30 dagers reinnleggelse etter sykehusopphold. Resultater for sykehus og kommuner 2016. Notat – Kvalitetsmåling – ISBN 978-82-8082-867-5. (English title: The quality indicator 30-day readmission after hospitalisation. Results for Norwegian hospital trusts and municipalities 2016). (2017)
(12) Hansen TM, Kristoffersen DT, Tomic O, Helgeland J. Kvalitetsindikatoren 30 dagers overlevelse etter sykehusinnleggelse. Resultater for 2016. Notat – Kvalitetsmåling – ISBN 978‐82‐8082‐866‐8. (English title: The quality indicator 30 day survival after hospital admission. Results for 2016). (2017)
(11) Saunes IS, Tomic O, Helgeland J, Lindahl AK. Helse i Norge – 2016: Kommentarrapport til OECDs sammenligning av europeiske land. ISBN 978-82-8082-793-7. (English title: Health in Norway – 2016: commentary report on OECD’s comparison of European countries). (2016)
(10) Hansen TM, Kristoffersen DT, Tomic O, Helgeland J. Kvalitetsindikatoren 30 dagers reinnleggelse etter sykehusopphold. Resultater for sykehus og kommuner 2015. Notat – Kvalitetsmåling – ISBN 978‐82‐8082‐766‐1. (English title: The quality indicator 30-day readmission after hospitalisation. Results for hospitals and municipalities 2015). (2016)
(09) Hansen TM, Kristoffersen DT, Tomic O, Helgeland J. Kvalitetsindikatoren 30 dagers overlevelse etter sykehusinnleggelse. Resultater for 2015. Notat – Kvalitetsmåling – ISBN 978-82-8082-757-9. (English title: The quality indicator 30 day survival after hospital admission. Results for 2015). (2016)
(08) Kristoffersen DT, Hansen TM, Lindman AS, Tomic O, Helgeland J. Kvalitetsindikatoren 30 dagers reinnleggelse etter sykehusopphold. Resultater for sykehus og kommuner 2014. Notat – Kvalitetsmåling – ISBN 978‐82‐8082‐720‐3. (English title: The quality indicator 30‐day readmission – results for Norwegian hospitals and municipalities 2014). (2015)
(07) Lindman AS, Tomic O, Kristoffersen DT, Helgeland J. 30-dagers overlevelse. Institusjonsrapport for norske sykehus for 2014. Notat – Kvalitetsmåling – des 2015. ISBN 978-82-93479-04-8. (English title: 30-day survival. Institution report for Norwegian hospitals for 2014). (2015)
(06) Lindman AS, Kristoffersen DT, Hansen TM, Tomic O, Helgeland J. Kvalitetsindikatoren 30-dagers overlevelse etter innleggelse i norske sykehus – resultater for året 2014. ISBN 978-82-93479-01-7. (English title: Quality indicator 30-days survival after admission to Norwegian hospitals). (2015)
(05) Saunes IS, Tomic O, Helgeland J, Lindahl AK. Norsk helsetjeneste sammenliknet med andre OECD-land 2015. ISBN 978-82-8121-996-0. (English title: The Norwegian health care system as compared to other OECD countries 2015). (2015)
(04) Lindman AS, Hassani S, Kristoffersen DT, Tomic O, Helgeland J. 30-dagers reinnleggelse av eldre 2011–2013. Resultater for sykehus og kommuner. Notat – Kvalitetsmåling – may 2015. ISBN 978-82-8121-950-2. (English title: Readmission of elderly patients within 30 days. Results for hospitals and municipalities). (2015)
(03) Lindman AS, Tomic O, Hassani S, Kristoffersen DT, Helgeland J. 30-dagers overlevelse. Institusjonsrapport for norske sykehus for 2013 – 2. utgave. Notat – Kvalitetsmåling – feb 2015. ISBN 978-82-8121-940-3. (English title: 30-day survival. Institution report for Norwegian hospitals for 2013 – 2nd edition). (2015)
(02) Lindman AS, Tomic O, Hassani S, Kristoffersen DT, Helgeland J. 30-dagers overlevelse. Institusjonsrapport for norske sykehus for 2013. Notat – Kvalitetsmåling – des 2014. ISBN 978-82-8121-932-8. (English title: 30-day survival. Institution report for Norwegian hospitals for 2013). (2014)
(01) A.S. Lindman, S. Hassani, D.T. Kristoffersen, O. Tomic, T. Dimoski, J. Helgeland. 30-dagers overlevelse og reinnleggelse ved norske sykehus for 2013. Notat – Kvalitetsmåling – 2014. ISBN 978-82-8121-912-0. (English title: 30-day survival and re-admission at Norwegian hospitals for 2013). (2014)
POPULAR SCIENCE ARTICLES
(03) By Invitation: O. Tomic. Using sensometrics to extract information from your sensory data. Journal of the Institute of Food Science and Technology, Volume 26-1, March 2012, 46-48 [more]
(02) A. Ådland Hansen, O. Tomic, S. Langsrud, M. Esaiassen, T. Næs, M. Rødbotten. Hvordan samsvarer mikrobiologiske metoder og TMA med forbrukernes preferanse av fersk-fisk kvalitet?, Norsk Sjømat, 5-2010, 20 – 22 [more]
(01) M. Rødbotten, J. Skaret, M. Esaiassen, M. Carlehøg, O. Tomic, P. Lea, T. Næs, J. Østli. Fersk torskefilet med en kvalitet som forbrukere vil ha: Hvordan kan den beskrives sensorisk?, Norsk Sjømat, 5-2010, 32 – 34 [more]
CONFERENCE POSTERS
(20) V.W.K. Tan, M.S.M Wee, O. Tomic, C.G. Forde. 13th Pangborn Sensory Science Symposium: “Engange with the Future”. 28 July – 1 August 2019, Edinburgh, UK. Psychophysical, Temporal and Qualitative Differences Among Sweeteners
(19) Y. Mardal Moe, A. Rossvoll Groendahl, M. Mulstad, O. Tomic, U. Indahl, E. Dale, E. Malinen, C. Futsaether. International Conference on Medical Imaging with Deep Learning, 08-10 July, London, UK. Deep learning for automatic tumour segmentation in PET/CT images of patients with head and neck cancers
(18) S. Langberg, A. Rosvoll Groendahl, A. Midtfjord, O. Tomic, K. Hovde Liland, I. Skjei Knudtsen, E. Dale, E. Malinen, C. Futsæther, Biology-Guided Adaptive Radiotherapy 2019 (BIGART 2019), 22-24 May, Aarhus, Denmark. Establishing a complete radiomics framework for biomarker identification and outcome prediction using PET/CT images of head & neck cancers
(17) A. Rossvoll Groendahl, I. Skjei Knudtsen, M. Mulstad, O. Tomic, Y. Mardal Moe, U. Indahl, T. Torheim, E. Dale, E. Malinen, C. Futsæther, Biology-Guided Adaptive Radiotherapy 2019 (BIGART 2019), 22-24 May, Aarhus, Denmark. Automatic tumour delineation of head and neck cancers in PET/CT images using thresholding and machine learning methods
(16) A. Rossvoll Groendahl, I. Skjei Knudtsen, M. Mulstad, O. Tomic, Y. Mardal Moe, U. Indahl, T. Torheim, E. Dale, E. Malinen, C. Futsæther, Biology-Guided Adaptive Radiotherapy 2019 (BIGART 2019), 22-24 May, Aarhus, Denmark. Automatic tumour delineation of head and neck cancers in PET/CT images using thresholding and machine learning methods
(15) A. Rossvoll Grøndahl, M. Mulstad, Y. Mardal Moe, I. Skjei Knudtsen, T. Torheim, O. Tomic, U.G. Indahl, E. Malinen, E. Dale, C.M. Futsæther, Estro 38, 26-30 April, Milan, Italy. Comparison of automatic tumour segmentation approaches for head and neck cancers in PET/CT images
(14) J. Helgeland, O. Tomic, T.M. Hansen, D.T. Kristoffersen, S. Hassani, A.K. Lindahl; ISQua 35th International Conference, 23-26 September 2018, Kuala Lumpur, Malaysia, Is wound dehiscence after laparotomy a useful indicator of patient safety for Norwegian hospitals?
(13) A. Kuznetsova, P.B. Brockhoff, T. Næs, O. Tomic; Eurosense 2014 – A sense of Life; 7-10 September 2014, Copenhagen, Denmark; ConsumerCheck: a free software for analysis of consumer acceptance data
(12) S. Grimsby, Ø. Ueland, A. Segtnan, O. Tomic, A. Kigen, T. Angelsen; 6th edition of EGEA Conference: Social and Health Benefits of Balance Diet: The role of Fruits and Vegetables; 5-7 May 2010, Brussels, Belgium; Understanding school children’s preferences for apple varieties in order to provide variation and promote consumption of Norwegian apples
(11) Ø. Ueland, A. Segtnan, O. Tomic; 9th Pangborn Sensory Symposium; 26-30 July 2009, Florence, Italy; Bringing sensory science into cultivation practices – a case of potato quality [more]
(10) B.S. Granli, O. Tomic, J. Skaret, S. Sahlström, M. Rødbotten; 9th Pangborn Sensory Symposium; 26-30 July 2009, Florence, Italy; Barley bread with low content of salt: a cross cultural study in several European countries [more]
(09) O. Tomic, C. Forde, A. Segtnan, M. Rødbotten, A. Nilsen, C. Delahunty, T. Næs; 9th Pangborn Sensory Symposium; 26-30 July 2009, Florence, Italy; Evaluating the influence of performance feedback on trained sensory panel performance in training sessions [more]
(08) O. Tomic, C. Forde, C. Delahunty, T. Næs; Eurosense 2008 – A sense of innovation; 7-10 September 2008, Hamburg, Germany; PCA-based performance indices for measuring sensory panel performance in training sesions
(07) A. Nilsen, O. Tomic, T. Næs; 7th Pangborn Sensory Symposium; 12-16 August 2007, Minneapolis, MN, USA; Use of PanelCheck to compare panel performance from inter collaborative test
(06) O. Tomic, M. Martens, H. Martens, T. Næs; Sensometrics 2006 – Imagine the senses; 1-3 August 2006, Ås, Norway; Scaling effects in sensory profiling
(05) T. Dahl, O. Tomic, A. Nilsen, J.P. Wold, T. Næs; 6th Pangborn Sensory Symposium; 7-11 August 2005, Harrogate, England; Some new tools for visualising multivariate and multiway data
(04) O. Tomic, M. Kermit; 3rd International Conference on Independent Component Analysis and Blind Signals Separation (ICA 2001), 9-12 December 2001, San Diego, CA, USA; Independent components of odour signals
(03) M. Kermit, O. Tomic; 3rd International Conference on Independent Component Analysis and Blind Signals Separation (ICA 2001), 9-12 December 2001, San Diego, CA, USA; Increased discrimination between odor signals by independent component analysis
(02) O. Tomic, J.E. Haugen, F. Lundby; Electronic Nose Technologies – Advances in Engineering, Integrating and Commercializing Novel Sensor Technologies (The Knowledge Foundation); 26-27 October 2000, San Diego, CA, USA; Measurement of lipid oxidation in marine fish oils by a commercial sensor array system
(01) J.-E. Haugen, O. Tomic, F. Lundby, F. Strand, E. Svela, K. Jørgensen; ISOEN 2000; 20-24 July 2000, Brighton, England; Analysis of off-flavours in raw cows milk with a commercial gas-sensor array
Oliver Tomic 