D-Index & Metrics Best Publications
Sabine Van Huffel

Sabine Van Huffel

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 53 Citations 14,005 388 World Ranking 1159 National Ranking 13

Research.com Recognitions

Awards & Achievements

2016 - SIAM Fellow For bridging the gap between advanced numerical linear algebra techniques and biomedical signal processing.

2009 - IEEE Fellow For contributions to total least squares fitting and computational biosignal processing

Overview

What is she best known for?

The fields of study she is best known for:

  • Internal medicine
  • Statistics
  • Artificial intelligence

Sabine Van Huffel focuses on Total least squares, Algorithm, Artificial intelligence, Electroencephalography and Singular value decomposition. Her Total least squares research includes themes of Estimation theory, Generalized least squares, Mathematical optimization and Applied mathematics. Sabine Van Huffel has researched Algorithm in several fields, including Time domain, Signal, Signal processing, Nonlinear system and Nuclear magnetic resonance.

Her work deals with themes such as Machine learning, Magnetic resonance imaging and Pattern recognition, which intersect with Artificial intelligence. Her work carried out in the field of Electroencephalography brings together such families of science as Artifact, Independent component analysis and Epilepsy. Her Singular value decomposition research includes elements of Linear prediction, Overdetermined system and Numerical linear algebra.

Her most cited work include:

  • Improved Method for Accurate and Efficient Quantification of MRS Data with Use of Prior Knowledge (1281 citations)
  • The Total Least Squares Problem: Computational Aspects and Analysis (1103 citations)
  • Overview of total least-squares methods (556 citations)

What are the main themes of her work throughout her whole career to date?

Her scientific interests lie mostly in Artificial intelligence, Pattern recognition, Electroencephalography, Algorithm and Internal medicine. She has included themes like Machine learning, Speech recognition and Computer vision in her Artificial intelligence study. Electroencephalography connects with themes related to Epilepsy in her study.

Her Algorithm study focuses mostly on Total least squares and Singular value decomposition. The Total least squares study combines topics in areas such as Generalized least squares, Numerical linear algebra, Applied mathematics and Non-linear least squares. Her Internal medicine study combines topics from a wide range of disciplines, such as Oncology and Cardiology.

She most often published in these fields:

  • Artificial intelligence (27.09%)
  • Pattern recognition (19.96%)
  • Electroencephalography (13.38%)

What were the highlights of her more recent work (between 2015-2021)?

  • Artificial intelligence (27.09%)
  • Pattern recognition (19.96%)
  • Electroencephalography (13.38%)

In recent papers she was focusing on the following fields of study:

Sabine Van Huffel mostly deals with Artificial intelligence, Pattern recognition, Electroencephalography, Internal medicine and Cardiology. Her studies in Artificial intelligence integrate themes in fields like Machine learning and Magnetic resonance imaging. The various areas that she examines in her Pattern recognition study include Tensor, White matter, Non-negative matrix factorization and Sensitivity.

Her Electroencephalography research is multidisciplinary, incorporating elements of Neurovascular coupling, Audiology, Speech recognition, Kappa and Epilepsy. Her Cardiology research is multidisciplinary, relying on both Heart rate variability, Blood pressure, Heart rate and Disease. Sabine Van Huffel combines subjects such as Respiratory system and Respiration with her study of Heart rate.

Between 2015 and 2021, her most popular works were:

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
  • Reference values of regional cerebral oxygen saturation during the first 3 days of life in preterm neonates (88 citations)
  • Neonatal Seizure Detection Using Deep Convolutional Neural Networks. (71 citations)

In her most recent research, the most cited papers focused on:

  • Internal medicine
  • Statistics
  • Artificial intelligence

Sabine Van Huffel mainly investigates Artificial intelligence, Pattern recognition, Electroencephalography, Epilepsy and Magnetic resonance imaging. Her Artificial intelligence research integrates issues from Electrocardiography, Machine learning and Computer vision. Her work in Pattern recognition addresses subjects such as Random forest, which are connected to disciplines such as Test set.

Her Electroencephalography study combines topics in areas such as Audiology, Speech recognition, Kappa, Functional magnetic resonance imaging and Convolutional neural network. In her study, Respiration and Low complexity is inextricably linked to Heart rate, which falls within the broad field of Epilepsy. Her Smoothing research incorporates elements of Algorithm and Sleep.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The Total Least Squares Problem: Computational Aspects and Analysis

Sabine Van Huffel;Joos Vandewalle.
(1987)

2097 Citations

Improved Method for Accurate and Efficient Quantification of MRS Data with Use of Prior Knowledge

Leentje Vanhamme;Aad van den Boogaart;Sabine Van Huffel.
Journal of Magnetic Resonance (1997)

1753 Citations

Overview of total least-squares methods

Ivan Markovsky;Sabine Van Huffel.
Signal Processing (2007)

904 Citations

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
Unknown Journal (2018)

685 Citations

Antenatal Maternal Anxiety is Related to HPA-Axis Dysregulation and Self-Reported Depressive Symptoms in Adolescence: A Prospective Study on the Fetal Origins of Depressed Mood

Bea R H Van den Bergh;Ben Van Calster;Tim Smits;Sabine Van Huffel.
Neuropsychopharmacology (2008)

506 Citations

Review on solving the forward problem in EEG source analysis

Hans Hallez;Bart Vanrumste;Bart Vanrumste;Roberta Grech;Joseph Muscat.
Journal of Neuroengineering and Rehabilitation (2007)

486 Citations

Logistic Regression Model to Distinguish Between the Benign and Malignant Adnexal Mass Before Surgery: A Multicenter Study by the International Ovarian Tumor Analysis Group

Dirk Timmerman;Antonia Carla Testa;Tom Bourne;Enrico Ferrazzi.
Journal of Clinical Oncology (2005)

468 Citations

The total least squares problem

Sabine Van Huffel;H Zha.
(1993)

441 Citations

Total Least Squares and Errors-in-Variables Modeling : Analysis, Algorithms and Applications

Sabine Huffel;Philippe Lemmerling.
(2002)

380 Citations

The accuracy of transvaginal ultrasonography for the diagnosis of ectopic pregnancy prior to surgery

George Condous;Emeka Okaro;Asma Khalid;Chuan Lu.
Human Reproduction (2005)

372 Citations

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