Michael Biehl

About Michael Biehl

Michael Biehl, With an exceptional h-index of 44 and a recent h-index of 26 (since 2020), a distinguished researcher at Rijksuniversiteit Groningen, specializes in the field of machine learning, neural networks, artificial intelligence, statistical physics, biomedical data.

His recent articles reflect a diverse array of research interests and contributions to the field:

Forecasting relative returns for S&P 500 stocks using machine learning

Investigating the aspect of asymmetry in brain-first versus body-first Parkinson’s disease

Subspace corrected relevance learning with application in neuroimaging

Iterated Relevance Matrix Analysis (IRMA) for the identification of class-discriminative subspaces

Translating the potential of the urine steroid metabolome to stage NAFLD (TrUSt-NAFLD): study protocol for a multicentre, prospective validation study

Urine steroid metabolomics as a diagnostic tool in primary aldosteronism

Abstract: Urine steroid metabolomics as a diagnostic tool in endocrine hypertension

Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis

Michael Biehl Information

University

Position

Bernoulli Inst. for Mathematics Computer Science and Artificial

Citations(all)

9807

Citations(since 2020)

3899

Cited By

7607

hIndex(all)

44

hIndex(since 2020)

26

i10Index(all)

148

i10Index(since 2020)

66

Email

University Profile Page

Google Scholar

Michael Biehl Skills & Research Interests

machine learning

neural networks

artificial intelligence

statistical physics

biomedical data

Top articles of Michael Biehl

Forecasting relative returns for S&P 500 stocks using machine learning

Financial Innovation

2024/4/20

Michael Biehl
Michael Biehl

H-Index: 26

Nicolai Petkov
Nicolai Petkov

H-Index: 27

Investigating the aspect of asymmetry in brain-first versus body-first Parkinson’s disease

npj Parkinson's Disease

2024/3/30

Subspace corrected relevance learning with application in neuroimaging

Artificial Intelligence in Medicine

2024/3/1

Iterated Relevance Matrix Analysis (IRMA) for the identification of class-discriminative subspaces

Neurocomputing

2024/2/7

Michael Biehl
Michael Biehl

H-Index: 26

Translating the potential of the urine steroid metabolome to stage NAFLD (TrUSt-NAFLD): study protocol for a multicentre, prospective validation study

BMJ open

2024/1/1

Urine steroid metabolomics as a diagnostic tool in primary aldosteronism

The Journal of Steroid Biochemistry and Molecular Biology

2024/3/1

Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis

2023

Michiel Straat
Michiel Straat

H-Index: 3

Michael Biehl
Michael Biehl

H-Index: 26

Improved Interpretation of Feature Relevances: Iterated Relevance Matrix Analysis (IRMA)

2023/10

Michael Biehl
Michael Biehl

H-Index: 26

The Shallow and the Deep: A biased introduction to neural networks and old school machine learning

2023/9/27

Michael Biehl
Michael Biehl

H-Index: 26

Machine learning basic concepts for the movement disorders specialist

2023/5/23

Inge Tuitert
Inge Tuitert

H-Index: 3

Michael Biehl
Michael Biehl

H-Index: 26

Abstract: Machine learning-based steroid metabolome analysis reveals three distinct subtypes of polycystic ovary syndrome and implicates 11-oxygenated androgens as major …

Endocrine Abstracts

2023/5/2

Survey of feature selection and extraction techniques for stock market prediction

2023/1/12

Michael Biehl
Michael Biehl

H-Index: 26

Nicolai Petkov
Nicolai Petkov

H-Index: 27

Abstract: Off-line Learning Analysis for Soft Committee Machines with GELU Activation

2023

Michiel Straat
Michiel Straat

H-Index: 3

Michael Biehl
Michael Biehl

H-Index: 26

FDG-PET combined with Learning Vector Quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Computer Methods and Programs in Biomedicine

2022/10/1

Rick Van Veen
Rick Van Veen

H-Index: 3

Michael Biehl
Michael Biehl

H-Index: 26

A machine learning based approach to gravitational lens identification with the International LOFAR Telescope

Monthly Notices of the Royal Astronomical Society

2022/7/21

Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets

arXiv preprint arXiv:2206.02056

2022/6/4

19th SC@ RUG 2022 proceedings 2021-2022

2022/4/25

Michael Biehl
Michael Biehl

H-Index: 26

A learning vector quantization architecture for transfer learning based classification in case of multiple sources by means of null-space evaluation

2022/4/7

Michael Biehl
Michael Biehl

H-Index: 26

DECORAS: detection and characterization of radio-astronomical sources using deep learning

Monthly Notices of the Royal Astronomical Society

2022/3

See List of Professors in Michael Biehl University(Rijksuniversiteit Groningen)

Co-Authors

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