biomedicina slovenica

"Machine learning" : 125

  1. Lusa Lara
    Statistical and machine learning techniques
    2022 ►
  2. Virgolin Marco; Wang Ziyuan; Balgobind Brian; Dijk van Irma; Wiersma Jan; Kroon Petra S.; Janssens Geert O.; Herk Marcel van; Hodgson David C.; Zadravec-Zaletel Lorna
    Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy
    2020 ►
  3. Leskovar Tamara; Zupanič-Pajnič Irena; Jerman Ivan; Črešnar Matija
    ATR-FTIR spectroscopy as a pre-screening technique for the PMI assessment and DNA preservation in human skeletal remains ‐ a review
    2022 ►
  4. Kouter Katarina; Škrlj Blaž; Kuclar M; Bon Jurij; Videtič Paska Alja
    The use of machine learning in suicidal behaviour research
    2021 ►
  5. Bulloni Matteo; Sandrini Giada; Stacchiotti Irene; Barberis Massimo; Calabrese Fiorella; Carvalho Lina; Fontanini Gabriella; Alì Greta; Fortarezza Francesco; Hofman Paul; Kern Izidor
    Automated analysis of proliferating cells spatial organisation predicts prognosis in lung neuroendocrine neoplasms
    2021 ►
  6. Banić Ivana; Lovrić Mario; Cuder Gerald; Kern Roman; Rijavec Matija; Korošec Peter; Kljajić-Turkalj Mirjana
    Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children
    2021 ►
  7. Gupta Rajan; Pandey Gaurav; Pal Saibal K.
    Comparative analysis of epidemiological models for COVID-19 pandemic predictions
    2021 ►
  8. Colozza-Gama Gabriel A.; Callegari Fabiano; Bešić Nikola; Paviza Ana C. de J.; Cerutti Janete M.
    Machine learning algorithm improved automated droplet classification of ddPCR for detection of BRAF V600E in paraffin-embedded samples
    2021 ►
  9. Kukar Matjaž; Gunčar Gregor; Vovko Tomaž; Podnar Simon; Černelč Peter; Brvar Miran; Zalaznik Mateja; Notar Mateja; Moškon Sašo; Notar Marko
    COVID-19 diagnosis by routine blood tests using machine learning
    2021 ►
  10. Rocco Bernardo; Sighinolfi Maria Chiara; Sandri Marco; Spandri Valentina; Cimadamore Alessia; Volavšek Metka; Mazzucchelli Roberta; Lopez-Beltran Antonio; Eissa Ahmed; Bertoni Laura
    Digital biopsy with fluorescence confocal microscope for effective real-time diagnosis of prostate cancer
    2021 ►
  11. Troll Martina; Brandmaier Stefan; Reitmeier Sandra; Adam Jonathan; Sharma Sapna; Sommer Alice; Bind Marie-Abèle; Neuhaus Klaus; Clavel Thomas; Adamski Jerzy
    Investigation of adiposity measures and operational taxonomic unit (OTU) data transformation procedures in stool samples from a German cohort study using machine learning algorithms
    2020 ►
  12. Atabaki-Pasdar Naeimeh; Ohlsson Mattias; Viñuela Ana; Frau Francesca; Pomares-Millan Hugo; Haid Mark; Jones Angus G.; Thomas E. Louise; Koivula Robert W.; Adamski Jerzy
    Predicting and elucidating the etiology of fatty liver disease
    2020 ►
  13. Huang Jialing; Huth Cornelia; Covic Marcela; Troll Martina; Adam Jonathan; Zukunft Sven; Prehn Cornelia; Wang Li; Nano Jana; Adamski Jerzy
    Machine learning approaches reveal metabolic signatures of incident chronic kidney disease in individuals with prediabetes and type 2 diabetes
    2020 ►
  14. Ghaffari Morteza H.; Jahanbekam Amirhossein; Hassani Sadri; Schuh Katharina; Dusel Georg; Prehn Cornelia; Adamski Jerzy; Koch Christian; Sauerwein Helga
    Metabolomics meets machine learning
    2019 ►
  15. Deutsch Leon; Osredkar Damjan; Plavec Janez; Stres Blaž
    Spinal muscular atrophy after nusinersen therapy
    2021 ►
  16. Orešković Tin; Kujundžić Tiljak Mirjana
    Proactive machine-learning-based approaches to vaccine hesitancy for a potential SARS-Cov-2 vaccine
    2020 ►
  17. Bell Andrew; Rich Alexander; Teng Melisande; Orešković Tin; Bras Nuno B; Mestrinho Lénia; Golubovic Srdan; Pristaš Ivan; Zejnilović Leid
    Proactive advising
    2019 ►
  18. Kastrin Andrej; Hristovski Dimitar
    Scientometric analysis and knowledge mapping of literature-based discovery (1986-2020)
    2020 ►
  19. Videtič Paska Alja; Kouter Katarina
    Machine learning as the new approach in understanding biomarkers of suicidal behavior
    2020 ►
  20. Sudre Carole H.; Panovska-Griffiths Jasmina; Sanverdi Eser; Brandner Sebastian; Katsaros Vasileios K; Stranjalis George; Pizzini Francesca B.; Ghimenton Claudio; Šurlan Popović Katarina; Avsenik Jernej
    Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status
    2020 ►
  21. Jovchevska Ivana
    Next generation sequencing and machine learning technologies are painting the epigenetic portrait of glioblastoma
    2020 ►
  22. Podnar Simon; Kukar Matjaž; Gunčar Gregor; Notar Mateja; Gošnjak Nina; Notar Marko
    Diagnosing brain tumours by routine blood tests using machine learning
    2019 ►
  23. Leskovar Tamara; Zupanič-Pajnič Irena; Geršak Živa Miriam; Jerman Ivan; Črešnar Matija
    ATR-FTIR spectroscopy combined with data manipulation as a pre-screening method to assess DNA preservation in skeletal remains
    2020 ►
  24. Knific Tamara; Fishman Dmytro; Vogler Andrej; Gstöttner Manuela; Wenzl René; Peterson Hedi; Lanišnik-Rižner Tea
    Multiplex analysis of 40 cytokines do not allow separation between endometriosis patients and controls
    2019 ►
  25. Gorenjak Mario; Repnik Katja; Jezernik Gregor; Jurgec Staša; Skok Pavel; Potočnik Uroš
    Genetic prediction profile for adalimumab response in Slovenian Crohn's disease patients
    [Genetisches Vorhersageprofil für die Adalimumab-Antwort bei den slowenischen Morbus-Crohn-Patienten]
    2019 ►
  26. Osredkar Joško; Gosar David; Maček Jerneja; Kumer Kristina; Fabjan Teja; Finderle Petra; Šterpin Saša; Zupan Mojca; Jekovec-Vrhovšek Maja
    Urinary markers of oxidative stress in children with autism spectrum disorder (ASD)
    2019 ►
  27. Pečnik Klemen; Todorović Vesna; Bošnjak Maša; Čemažar Maja; Kononenko Igor; Serša Gregor; Plavec Janez
    The general explanation method with NMR spectroscopy enables the identification of metabolite profiles specific for normal and tumor cell lines
    2018 ►
  28. Xu Lina; Simjanovska Monika; Koteska Bojana; Trajkovski Vladimir; Bogdanova Ana Madevska; Drusany Starič Kristina; Lehocki Fedor
    Special section on trends, perspectives and prospects of machine learning applied to biomedical systems in internet of medical things
    2019 ►
  29. Perk Timothy; Bradshaw Tyler J.; Chen Song; Im Hyung-Jun; Cho Steve; Perlman Scott; Liu Glenn; Jeraj Robert
    Automated classification of benign and malignant lesions in 18F-NaF PET/CT images using machine learning
    2018 ►
  30. Zalar Bojan; Kores-Plesničar Blanka; Zalar Ina; Mertik Matej; Peterlin Borut
    Suicide and suicide attempt descriptors by multimethod approach
    2018 ►
  31. Listyowardojo Tita A.; Berglund Lars-Martin; Turk Eva
    Managing alarm systems for quality and safety in the hospital setting
    2018 ►
  32. Gunčar Gregor; Kukar Matjaž; Notar Mateja; Brvar Miran; Černelč Peter; Notar Manca; Notar Marko
    An application of machine learning to haematological diagnosis
    2018 ►
  33. Potočnik Uroš; Mitrovič Mitja; Repnik Katja; Štiglic Gregor; Weersma Rinse K.
    Machine learning algorithms based on genotype data predict subgroup of refractory Crohn's disease patients requiring biological therapy
    2015 ►
  34. Zorman Milan; Sánchez de la Rosa José Luis; Dinevski Dejan
    Classification of follicular lymphoma images
    2011 ►
  35. Zorman Milan; Pohorec Sandi; Butolen Bojan; Žlahtič Bojan; Kokol Peter
    Navzkrižno testiranje simboličnih in konektivističnih pristopov strojnemu učenju na specializiranih bazah akutnega vnetja slepiča
    [Cross-testing symbolic and connectionist machine learning approaches in specialized acute appendicitis databases]
    2012 ►
  36. Volk Marija; Maver Aleš; Lovrečić Luca; Juvan Peter; Peterlin Borut
    Expression signature as a biomarker for prenatal diagnosis of trisomy 21
    2013 ►
  37. Tao Dacheng
    ICMLA 2012
    2012 ►
  38. Groznik Vida; Guid Matej; Sadikov Aleksander; Možina Martin; Georgiev Dejan; Kragelj Veronika; Ribarič Samo; Pirtošek Zvezdan; Bratko Ivan
    Elicitation of neurological knowledge with ABML
    2011 ►
  39. Blagus Rok; Lusa Lara
    Evaluation of SMOTE for high-dimensional class-imbalanced microarray data
    2012 ►
  40. Lusa Lara; Blagus Rok
    The class-imbalance problem for hig-dimensional class prediction
    2012 ►
  41. Tao Dacheng
    ICMLA 2012. 11th International conference on machine learning and applications; 2012 Dec 12-15; Boca Raton
    2012 ►
  42. Groznik Vida; Guid Matej; Sadikov Aleksander; Možina Martin; Georgiev Dejan; Kragelj Veronika; Ribarič Samo; Pirtošek Zvezdan; Bratko Ivan
    Elicitation of neurological knowledge with argument-based machine learning
    2013 ►
  43. Grabnar Jera; Grošelj Ciril; Grošelj Urh
    Machine learning based expert system for SPECT myocardial perfusion scintigrams interpretation
    2010 ►
  44. Kononenko Igor; Kukar Matjaž; Grošelj Ciril
    Controlling the trade-off between the sensitivity and specificity in the diagnostics of the ischeamic heart disease
    1997 ►
  45. Anonymous ;
    Advanced seminar for professioanals Biomedical applications of computational logic and machine learning; 1997 Nov 11; Bled
    1997 ►
  46. Grošelj C; Kukar M; Fettich J; Kononenko I
    Machine learning improves the accuracy of coronary artery disease diagnostic methods
    1999 ►
  47. Panjan Andrej; Filipčič Aleš; Šarabon Nejc
    Application of machine learning methods in studies of tennis game profile
    2010 ►
  48. Križmarić Miljenko; Verlič Mateja; Štiglic Gregor; Grmec Štefek; Kokol Peter
    Intelligent analysis in predicting outcome of out-of-hospital cardiac arrest
    2009 ►
  49. Lenič Mitja; Zazula Damjan; Cigale Boris
    Obtaining completely stable cellular neural network templates for ultrasound image segmentation
    2007 ►
  50. Grošelj Kristina; Grošelj Jera; Mlinarič Mojca; Grošelj Urh
    Strojno učenje v interpretaciji rezultatov obremenitvene scintigrafije srčne mišice
    [Machine learning methods in interpretation of results of stress myocardial perfusion scintigraphy]
    2007 ►
  51. Kukar M; Grošelj C; Grošelj U
    Improving diagnostic process of coronary artery disease with multi-resolution image parametrization and machine learning
    2007 ►
  52. Leban Gregor; Zupan Blaž; Vidmar Gaj; Bratko Ivan
    VizRank: data visualization guided by machine learning
    2006 ►
  53. Jakulin A; Bratko I; Smrke D; Demšar J; Zupan B
    Attribute interactions in medical data analysis
    2003 ►
  54. Kobal-Grum Darja; Arnerič Niko; Kobal Alfred B; Horvat Milena; Ženko Bernard; Džeroski Sašo; Osredkar Joško
    Emotions and personality traits in former mercury miners
    [Čustva ter osebnostne lastnosti bivših rudarjev v rudniku živega srebra]
    2004 ►
  55. Kokol Peter; Mičetić-Turk Dušanka; Blažun Helena
    Integrating working experiences into nursing education with intelligent tools
    2005 ►
  56. Grošelj C; Kukar M; Fettich J; Kononenko I
    Machine learning improves the accuracy of coronary artery disease diagnostic methods
    1997 ►
  57. Kukar Matjaž; Grošelj Ciril
    Transductive machine learning for reliable medical diagnostics
    2005 ►
  58. Grošelj C; Kukar M
    Interpreting the results of myocardial perfusion scintigraphy by machine learning
    2004 ►
  59. Grošelj C; Kukar M
    Estimating the pretest probability of coronary artery disease by machine learning - comparison with the Diamond-Forrester method
    2004 ►
  60. Kokol Peter; Povalej Petra; Završnik Jernej
    Intelligent systems in nursing research
    2003 ►
  61. Ženko Bernard; Džeroski Sašo; Kobal Alfred B; Kobal-Grum Darja; Arnerić Niko; Osredkar Joško; Horvat Milena
    Relating personality traits and mercury exposure in miners with machine learning methods: a preliminary study
    2003 ►
  62. Curk Tomaž; Zupan Blaž; Vidmar Gaj
    Razvrščanje profilov izražanja genov z metodami strojnega učenja
    [Classification of gene expression profiles with machine learning]
    2003 ►
  63. Stankovski V; Bratko I; Demšar J; Smrke D
    Induction of hypotheses concerning hip arthroplasty: a modified methodology for medical research
    2001 ►
  64. Smith AE; Stankovski V; Marsh DM
    A comparison of two alternative methodologies for estimation of length of hospital stay
    2003 ►
  65. Gamberger D; Šmuc T; Lavrač N
    Subgroup discovery: on-line data mining server and its application
    2003 ►
  66. Molan Gregor; Molan Marija
    Formalization of expert AH model for machine learning
    2002 ►
  67. Grošelj C; Kukar M
    Machine learning improves the accuracy of myocardial perfusion scintigraphy results
    2002 ►
  68. Kukar Matjaž; Grošelj Ciril
    Reliable diagnostic for coronary artery disease
    2002 ►
  69. Leskošek Branimir
    Elektromiografija maternice med gravidnostjo pri človeku in ovci
    2002 ►
  70. Stankovski V; Smoth AE; Arnež ZM; Veselko M; Lopez JA; Young IR
    A decision tree model for length of stay in hospital
    2002 ►
  71. Grošelj C; Kukar M
    Improving the accuracy of myocardial perfusion scintigraphy results by machine learning method
    2002 ►
  72. Kokol Peter; Zorman Milan; Eich Hans-Peter; Ohmann Christian
    The difficulties of decision trees in the diagnostic of acute abdominal pain
    2001 ►
  73. Lavrač Nada; Kononenko Igor; Keravnou Elpida; Kukar Matjaž; Zupan Blaž
    Intelligent data analysis for medical diagnosis: using machine learning and temporal abstraction
    1998 ►
  74. Lukačić Zoran; Kern Josipa; Težak-Benčić Marija
    Detecting predictors of new-born survival by fuzzy sets based machine learning system
    2000 ►
  75. Robnik-Šikonja Marko; Kononenko Igor
    Attribute dependencies, understandability and split selection in tree based models
    1999 ►
  76. Pompe Uroš
    Noise-tolerant recursive best-first induction
    1999 ►
  77. Mladenić Dunja; Grobelnik Marko
    Feature selection for unbalanced class distribution and naive Bayes
    1999 ►
  78. Gamberger Dragan; Lavrač Nada; Grošelj Ciril
    Experiments with noise filtering in a medical domain
    1999 ►
  79. Bratko Ivan; Džeroski Sašo
    Machine learning. Proceedings of the 16th international conference (ICML'99); 1999 Jun 27-30; Bled
    1999 ►
  80. Grošelj C; Kukar M; Fettich JJ; Kononenko I
    Machine learning in the diagnosis of ischaemic heart disease
    1997 ►
  81. Lavrač N
    Selected techniques for data mining in medicine
    1999 ►
  82. Kukar Matjaž; Grošelj Ciril
    Machine learning in stepwise diagnostic process
    1999 ►
  83. Kononenko Igor
    A counter example to the stronger version of the binary tree hypothesis
    1995 ►
  84. Kononenko Igor
    Estimating attributes: analysis and extensions of RELIEF
    1994 ►
  85. Kukar Matjaž; Kononenko Igor; Grošelj Ciril; Kralj Katarina; Fettich Jure
    Analysing and improving the diagnosis of ischaemic heart disease with machine learning
    1999 ►
  86. Stankovski V
    The use of artificial intelligence in interpretation of clinical trials
    1998 ►
  87. Grošelj Ciril
    Sistem nevronskih mrež v diagnostiki ishemične bolezni srca
    1999 ►
  88. Zelič Igor; Lavrač Nada
    Impact of machine learning to the diagnosis and prognosis of first cerebral paroxysm
    1999 ►
  89. Zrimec Tatjana; Sammut Claude
    The potential for machine learning in medical image processing
    1997 ►
  90. Bajd T; Grobelnik M; Mladenić D; Lavrač N; Prodnik V; Benko H; Šavrin R; Obreza P
    Machine learning for prediction of walking abilities in incomplete spinal cord injured patients
    1997 ►
  91. Bajd T; Kralj A; Štefančič M; Lavrač N
    FES assisted walking in incomplete SCI subjects: an overview
    1998 ►
  92. Zelič Igor; Kononenko Igor; Lavrač Nada; Vuga Vanja
    Diagnosis of sport injuries with machine learning: explanatation of induced decisions
    1997 ►
  93. Zelič Igor; Kononenko Igor; Lavrač Nada; Vuga Vanja
    Machine learning applied to diagnosis of sport injuries
    1997 ►
  94. Zupan Blaž; Džeroski Sašo
    Acquiring and validating background knowledge for machine learning using function decomposition
    1997 ►
  95. Zupan Blaž; Stokić Dobrivoje S; Bohanec Marko; Priebe Michael M; Sherwood Arthur M
    Relating clinical and neurophysiological assesment of spasticity by machine learning
    1997 ►
  96. Kononenko Igor; Bratko Ivan; Kukar Matjaž
    Application of machine learning to medical diagnosis
    1998 ►
  97. Šter Branko; Kukar Matjaž; Dobnikar Andrej; Kranjec Igor; Kononenko Igor
    Experiments with machine learning in the prediction of coronary artery disease progression
    1997 ►
  98. Kukar Matjaž; Bešič Nikola; Kononenko Igor; Auersperg Marija; Robnik-Šikonja Marko
    Prognosing the survival time of patients with anaplastic thyroid carcinoma using machine learning
    1997 ►
  99. Kukar Matjaž; Kononenko Igor; Silvester Tomaž
    Machine learning in prognosis of the femoral neck fracture recovery
    1996 ►
  100. Šter Branko; Kukar Matjaž; Dobnikar Andrej; Kranjec Igor; Kononenko Igor
    Experiments with machine learning in the prediction of coronary artery disease progression
    1996 ►

1 101  


New search      Comments      Top of page Institute for Biostatistics and Medical Informatics