Karel Hron
2 Papers
Karel Hron is an academic researcher. The author has contributed to research in topics: Microbiome & Computer science. The author has an hindex of 2, co-authored 2 publications.
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Papers
Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment.
Laura Judith Marcos-Zambrano,Kanita Karaduzovic-Hadziabdic,Tatjana Loncar Turukalo,Piotr Przymus,Vladimir Trajkovik,Oliver Aasmets,Magali Berland,Aleksandra Gruca,Jasminka Hasic,Karel Hron,Thomas Klammsteiner,Mikhail Kolev,Leo Lahti,Marta B. Lopes,Victor Moreno,Irina Naskinova,Elin Org,Inês Paciência,Georgios Papoutsoglou,Rajesh Shigdel,Blaz Stres,Baiba Vilne,Malik Yousef,Eftim Zdravevski,Ioannis Tsamardinos,Enrique Carrillo de Santa Pau,Marcus J. Claesson,Isabel Moreno-Indias,Isabel Moreno-Indias,Jaak Truu +29 more
TL;DR: In this paper, a review of the state-of-the-art ML methods and respective software applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities, is presented.
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.
Isabel Moreno-Indias,Isabel Moreno-Indias,Leo Lahti,Miroslava Nedyalkova,Ilze Elbere,Gennady V. Roshchupkin,Muhamed Adilovic,Onder Aydemir,Burcu Bakir-Gungor,Enrique Carrillo de Santa Pau,Domenica D'Elia,Mahesh Desai,Laurent Falquet,Laurent Falquet,Aycan Gundogdu,Karel Hron,Thomas Klammsteiner,Marta B. Lopes,Laura Judith Marcos-Zambrano,Cláudia Marques,Michael Mason,Patrick May,Lejla Pašić,Gianvito Pio,Sándor Pongor,Vasilis J. Promponas,Piotr Przymus,Julio Saez-Rodriguez,Alexia Sampri,Rajesh Shigdel,Blaz Stres,Blaz Stres,Ramona Suharoschi,Jaak Truu,Ciprian-Octavian Truica,Baiba Vilne,Dimitrios Vlachakis,Ercument Yilmaz,Georg Zeller,Aldert Zomer,David Gomez-Cabrero,Marcus J. Claesson +41 more
TL;DR: The COST Action CA18131 "ML4Microbiome" as discussed by the authors brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.