February 7, 2024:
January 30, 2024:
January 5, 2024:
December 2023:
November 2023:
Friday, March 24, 2023: WISCI
March 2023:
Otavio Citon
January 2023:
Roland Veen
December 2022: Michiel Straat
defended his PhD thesis (with distinction)
October 2022:
June 2022:
Frederieke
Richert joined the group as a PhD student
June 2022: Samira Rezaei
defended her PhD thesis
May 2022: Rick van Veen
defended his PhD thesis
October 2021:
LVQ toolbox revised and new sklvq package available
The no-nonsense (GM)LVQ toolbox has been revised for matlab (R2021)
by Roland Veen, see here.
Rick van Veen's
sklearn compatible sklvq package is documented also in a
recent (open access) publication:
October 2021: Michele
Mastropietro defended his PhD
September 2021: Sreejita Ghosh
defended her PhD thesis
July 2021:
June 2021:
April 2021:
March 2021:
March 2021:
Our paper in
The Lancet Diabetes and Endocronology
on Urine Steroid Metabolomics
February 01, 2021:
Honorary Professorship
January 26, 2021:
Best PhD Thesis Award for Godliver Owomugisha
December 18, 2020:
100 journal publications
November 23, 2020:
RUG online magazine
November 2020:
November 2020:
October 19, 2020:
David Nebel
defended his PhD thesis
October 8, 2020:
DSA Research Award for Godliver Owomugisha
September 2020:
August 28, 2020:
Godliver Owomugisha defended her PhD thesis
July 2020:
Our publication in Neurocomputing is online (open access):
Iterated Relevance Matrix (IRMA) for the identification of class-discriminative subspaces
Neurocomputing 577: Art. No. 127367 (2024)
Our publication in AIM is online (open access):
Subspace corrected relevance learning with application
in neuroimaging
Artificial Intelligence in Medicine 149: Art. No. 102786 (2024)
After about 6 months, at last, the Editorial Board of the MDPI journal
Applied Sciences retracted
a completely plagiarized article, see
retracted article,
retraction note
The "authors" blatantly copy/pasted, manipulated and re-interpreted
figures and equations from our work. The retraction process and communication
with the Editorial Office was painful and took much too long.
An application of interpretable machine learning (GMLVQ) in endocrinology
Urine steroid metabolomics as a diagnostic tool in primary aldosteronism
J. Steroid Biochemistry and Molecular Biology 237: 106445 (2023)
(open access)
Our general, basic introduction to machine learning
Machine
learning basic concepts for the movement disorders specialist
International Review of Movement Disorders, Vol. 5, 2023
is available through the University of Groningen.
International Workshop on Intelligent Systems
and Computational Intelligence 2023
Speakers from Bielefeld University, Hochschule Mittweida and
Bernoulli Institute
Details and program
has joined as a PhD students. Welcome to the group!
Otavio will work on the statistical physics of learning in layered
networks
has joined as a PhD students. Welcome to the group!
Roland will work on the analysis of steroid metabolomics
data.
Machine learning: statistical physics based theory and smart industry applications
Congratulations, Dr. Michiel :-)
Publication in Computer Methods and Programs in Biomedicine available online (open access)
FDG-PET combined with learning vector quantization allows classification of neurodegenerative
diseases and reveals the trajectory of idiopathic REM sleep behavior disorder
She will work on the NWO funded project
The Role of the Activation Function in Feedforward Learning Systems (RAFFLES)
Deep learning in high angular-resolution radio interferometry
first supervisor:
John McKean
Congratulations, Dr. Samira :-)
Learning Vector Quantization with Applications in Neuroimaging and Biomedicines
co-supervisors:
Nico Leenders,
Nicolai Petkov
Congratulations, Dr. Rick :-)
JMLR, vol. 22, issue 231, pp. 1-6.
Numerical
simulations of dwarf galaxies in the Fornax cluster
and obtained a double degree with Ghent University, Belgium.
The project was completed under main supervsion by Sven de Rijcke (Ghent).
Congratulations, Dr. Michele!
Intrinsically Interpretable Machine Learning in
Computer Aided Diagnosis
completed under the main supervsion by
Kerstin Bunte
Congratulations, Dr. Sreejita :-)
Google AI for Social Good
supports the project
Adoption of smartphone agro-applications for field-based disease diagnosis
and real-time feedback for smallholder farmers
of former PhD student
Godliver Owomugisha
and the Papoli Community Development Foundation
IEEE Access
The paper
Matrix
Relevance Learning From Spectral Data for Diagnosing Cassava Diseases
has been published (open access) in IEEE Access, Volume 9, pp. 83355-83363, 2021,
doi: 10.1109/ACCESS.2021.308723
25 May 2021:
M. Biehl gave an invited talk at the
23rd European Congress of Endocrinology eECE2021:
Interpretable machine learning models in endocrinology (and beyond)
Neural Computing and Applications (NCAA)
The paper
Supervised learning in the presence of concept drift: a modelling framework
has been published in a special issue
of NCAA
and is available online (open access)
Annals of Surgery: online publication ahead of print (2021)
Comment on ''A Modern Assessment of Cancer Risk in Adrenal Incidentalomas''
V. Chortis, A.J. Sitch, I. Bancos, A. Prete, A.E. Taylor, M. Biehl, J.J. Deeks, W. Arlt
for the detection of adrenal cancer
in adrenal incidentalomas was acknowledged as top advance
in 2020
by
Endocrinology and Metabolism.
I have been awarded the title of Honorary Professor of Machine
Learning at the
Institute
of Metabolism and Systems Research
(ISMR) of
the University of Birmingham/UK.
Godliver Owomugisha has won the
2020 Best Thesis Award
of the Groningen Engineering Center for her thesis
Computational
Intelligence and modeling crop disease data in Africa
The list of my 100 most important journal publications :-) now available.
published a nice piece on our longstanding collaboration in machine
learning and steroid metabolomcis
with the
Medical School, University of Birmingham, UK.
Smart algorithm improves diagnosis of adrenal tumours
(by Rene Fransen)
Physica A: Statistical Mechanics and its Applications Vol. 564, 2021, 125517 (open access)
Hidden unit specialization in layered
neural networks: ReLU vs. sigmoidal activation
Elisa Oostwal, Michiel Straat, Michael Biehl
Our systematic comparison of networks with
ReLU and sigmoidal units in model
situations
reveals surprising differences in their training and generalization
behavior.
Frontiers in Applied Mathematics
and Statistics Vol. 6, 56, 2020 (open access)
Data-Driven
Supervised Learning for Life Science Data
Maximilian Münch, Christoph Raab, Michael Biehl, Frank-Michael Schleif
Median Variants of Prototype Based
Learning Vector Quantization
Congratulations Dr. David :-)
The project Early detection and diagnosis of crop diseases in
asymptomatic plants:
acquisition and machine learning analysis of
spectral data
will be supported by
Data Science Africa.
This will enable us to continue our collaboration with the
National Crops Resources Research Institute (NaCRRI) of Uganda
in the diagnosis and monitoring of cassava disease.
Computer Methods and Programs in Biomedicine
Vol. 197, 2020, 105708 (open access)
An application of Generalized Matrix Learning
Vector Quantization in Neuroimaging
R. van Veen, V. Gurvits, R.V. Kogan, S.K. Meles, G.-J. de Vries, R.J. Renken,
M.C. Rodriguez-Oroz, R. Rodriguez-Rojas, D. Arnaldi, S. Raffa, B.M. de Jong,
K.L. Leenders, M. Biehl
Computational
Intelligence and modeling crop disease data in Africa
Congratulations Dr. Godliver :-)
The Lancet Diabetes and Endocrinology
Vol. 8, issue 9, 773-781, 2020 (open access)
Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas
in the EURINE-ACT study: a prospective test validation study
I. Bancos, A. Taylor, V. Chortis, A. Sitch et al.
DOI: 10.1016/S2213-8587(20)30218-7 (pdf), also:
PubMed.gov