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ORCIDMattias Ohlsson
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2020 – today
- 2024
[j19]Abdallah Alabdallah
, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson:
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models. Artif. Intell. Medicine 148: 102781 (2024)- [c17]Mohammed Ghaith Altarabichi, Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Mattias Ohlsson:
Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks. GECCO Companion 2024: 1863-1869 - [c16]Abdallah Alabdallah, Jakub Jakubowski, Sepideh Pashami, Szymon Bobek, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Grzegorz J. Nalepa:
Understanding Survival Models Through Counterfactual Explanations. ICCS (4) 2024: 310-324 - [c15]Atiye Sadat Hashemi, Mirfarid Musavian Ghazani, Mattias Ohlsson, Jonas Björk, Dominik Dietler:
Surveillance of Disease Outbreaks Using Unsupervised Uni-Multivariate Anomaly Detection of Time-Series Symptoms. MIE 2024: 1916-1920 - [i9]Ali Amirahmadi, Mattias Ohlsson, Kobra Etminani, Olle Melander, Jonas Björk:
A Masked language model for multi-source EHR trajectories contextual representation learning. CoRR abs/2402.06675 (2024) - [i8]Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Sepideh Pashami:
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis. CoRR abs/2407.13849 (2024) - 2023
- [j18]Ali Amirahmadi, Mattias Ohlsson, Kobra Etminani:
Deep learning prediction models based on EHR trajectories: A systematic review. J. Biomed. Informatics 144: 104430 (2023) - [j17]Pontus Olsson de Capretz, Anders Björkelund, Jonas Björk, Mattias Ohlsson, Arash Mokhtari, Axel Nyström, Ulf Ekelund:
Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation. BMC Medical Informatics Decis. Mak. 23(1): 25 (2023) - [c14]Hamid Sarmadi, Thorsteinn S. Rögnvaldsson, Nils Roger Carlsson, Mattias Ohlsson, Ibrahim Wahab, Ola Hall:
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks. DSAA 2023: 1-10 - [c13]Ali Amirahmadi, Mattias Ohlsson, Kobra Etminani, Olle Melander, Jonas Björk:
A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning. MIE 2023: 609-610 - [i7]Hamid Sarmadi, Thorsteinn S. Rögnvaldsson, Nils Roger Carlsson, Mattias Ohlsson, Ibrahim Wahab, Ola Hall:
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks. CoRR abs/2312.00416 (2023) - 2022
- [j16]Jennifer David, Thorsteinn S. Rögnvaldsson, Bo Söderberg, Mattias Ohlsson:
Deterministic annealing with Potts neurons for multi-robot routing. Intell. Serv. Robotics 15(3): 321-334 (2022) - [j15]Ola Hall, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson:
A review of explainable AI in the satellite data, deep machine learning, and human poverty domain. Patterns 3(10): 100600 (2022) - [c12]Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Mattias Ohlsson:
SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP. DSAA 2022: 1-10 - [i6]Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson:
The Concordance Index decomposition: a measure for a deeper understanding of survival prediction models. CoRR abs/2203.00144 (2022) - [i5]Ola Hall, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson:
Satellite Image and Machine Learning based Knowledge Extraction in the Poverty and Welfare Domain. CoRR abs/2203.01068 (2022) - 2020
- [j14]Alexander Galozy, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Mattias Ohlsson, Markus Lingman:
Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation. Int. J. Medical Informatics 136: 104092 (2020) - [i4]Najmeh Abiri, Mattias Ohlsson:
Variational auto-encoders with Student's t-prior. CoRR abs/2004.02581 (2020) - [i3]Najmeh Abiri, Björn Linse, Patrik Edén, Mattias Ohlsson:
Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems. CoRR abs/2004.02584 (2020) - [i2]Alexander Galozy, Slawomir Nowaczyk, Mattias Ohlsson:
Corrupted Contextual Bandits with Action Order Constraints. CoRR abs/2011.07989 (2020)
2010 – 2019
- 2019
- [j13]Najmeh Abiri, Björn Linse, Patrik Edén, Mattias Ohlsson:
Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems. Neurocomputing 365: 137-146 (2019) - [c11]Najmeh Abiri, Mattias Ohlsson:
Variational auto-encoders with Student's t-prior. ESANN 2019 - 2017
- [c10]Anna Gummeson, Ida Arvidsson, Mattias Ohlsson, Niels Christian Overgaard, Agnieszka Krzyzanowska, Anders Heyden, Anders Bjartell, Kalle Åström:
Automatic Gleason grading of H and E stained microscopic prostate images using deep convolutional neural networks. Medical Imaging: Digital Pathology 2017: 101400S - 2014
- [j12]Jonas Kalderstam, May Sadik, Lars Edenbrandt, Mattias Ohlsson:
Analysis of regional bone scan index measurements for the survival of patients with prostate cancer. BMC Medical Imaging 14: 24 (2014) - 2013
- [j11]Jonas Kalderstam, Patrik Edén, Pär-Ola Bendahl, Carina Strand, Mårten Fernö, Mattias Ohlsson:
Training artificial neural networks directly on the concordance index for censored data using genetic algorithms. Artif. Intell. Medicine 58(2): 125-132 (2013) - [j10]Jose Teles, Cristina Pina, Patrik Edén, Mattias Ohlsson, Tariq Enver, Carsten Peterson:
Transcriptional Regulation of Lineage Commitment - A Stochastic Model of Cell Fate Decisions. PLoS Comput. Biol. 9(8) (2013) - [c9]Jonas Kalderstam, Patrik Edén, Mattias Ohlsson:
Ensembles of genetically trained artificial neural networks for survival analysis. ESANN 2013 - 2011
- [c8]Matilda Landgren, Karl Sjöstrand, Mattias Ohlsson, Daniel Ståhl, Niels Chr. Overgaard, Kalle Åström, Rune Sixt, Lars Edenbrandt:
An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images. SCIA 2011: 489-500
2000 – 2009
- 2009
- [j9]Michael Green, Ulf Ekelund, Lars Edenbrandt, Jonas Björk, Jakob Lundager Forberg, Mattias Ohlsson:
Exploring new possibilities for case-based explanation of artificial neural network ensembles. Neural Networks 22(1): 75-81 (2009) - [c7]Mattias Ohlsson, Reza Kaboteh, May Sadik, Madis Suurkula, Milan Lomsky, Peter Gjertsson, Karl Sjöstrand, Jens Richter, Lars Edenbrandt:
Automated decision support for bone scintigraphy. CBMS 2009: 1-6 - [c6]Karl Sjöstrand, Mattias Ohlsson, Lars Edenbrandt:
Statistical Regularization of Deformation Fields for Atlas-Based Segmentation of Bone Scintigraphy Images. MICCAI (1) 2009: 664-671 - 2006
- [j8]Michael Green, Jonas Björk, Jakob Lundager Forberg, Ulf Ekelund, Lars Edenbrandt, Mattias Ohlsson:
Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room. Artif. Intell. Medicine 38(3): 305-318 (2006) - [j7]Jonas Björk, Jakob Lundager Forberg, Mattias Ohlsson, Lars Edenbrandt, Hans Öhlin, Ulf Ekelund:
A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department. BMC Medical Informatics Decis. Mak. 6: 28 (2006) - 2004
- [j6]Mattias Ohlsson:
WeAidU - a decision support system for myocardial perfusion images using artificial neural networks. Artif. Intell. Medicine 30(1): 49-60 (2004) - [j5]Henrik Haraldsson, Lars Edenbrandt, Mattias Ohlsson:
Detecting acute myocardial infarction in the 12-lead ECG using Hermite expansions and neural networks. Artif. Intell. Medicine 32(2): 127-136 (2004) - 2003
- [c5]Flore Gouaux, Lucas Simon Chautemps, Jocelyne Fayn, Stefano Adami, Mohammad Arzi, Deodato Assanelli, Marie-Claire Forlini, Cesare Malossi, Antonio Martinez, Mattias Ohlsson, Joël Placide, Gian-Luca Ziliani, Paul Rubel:
Pervasive Self-Care Solutions in Telecardiology. Typical use cases from the EPI-MEDICS project. MIE 2003: 119-124 - 2002
- [j4]Maximilian Schlosshauer, Mattias Ohlsson:
A novel approach to local reliability of sequence alignments. Bioinform. 18(6): 847-854 (2002) - 2001
- [j3]Mattias Ohlsson, Carsten Peterson, Bo Söderberg:
An efficient mean field approach to the set covering problem. Eur. J. Oper. Res. 133(3): 583-595 (2001) - 2000
- [c4]Andreas Järund, Lars Edenbrandt, Mattias Ohlsson, Erik Borälv:
Internet Based Artificial Neural Networks for the Interpretation of Medical Images. ANNIMAB 2000: 87-92 - [c3]Holger Holst, Lars Edenbrandt, Mattias Ohlsson, Hans Öhlin:
A New Artificial Neural Network Method for the Interpretation of ECGs. ANNIMAB 2000: 186-191 - [c2]Mattias Ohlsson, Holger Holst, Lars Edenbrandt:
Acute Myocardial Infarction: Analysis of the ECG Using Artificial Neural Networks. ANNIMAB 2000: 209-214
1990 – 1999
- 1999
- [c1]Mattias Ohlsson, Andreas Järund, Lars Edenbrandt:
WWW Based Service for Automated Interpretation of Diagnostic Imgages: The AIDI-Heart Project. HPCN Europe 1999: 941-950 - [i1]Mattias Ohlsson, Carsten Peterson, Bo Söderberg:
An Efficient Mean Field Approach to the Set Covering Problem. CoRR cs.NE/9902025 (1999) - 1997
- [j2]Mattias Ohlsson, Hong Pi:
A Study of the Mean Field Approach to Knapsack Problems. Neural Networks 10(2): 263-271 (1997) - 1993
- [j1]Mattias Ohlsson, Carsten Peterson, Bo Söderberg:
Neural Networks for Optimization Problems with Inequality Constraints: The Knapsack Problem. Neural Comput. 5(2): 331-339 (1993)
Coauthor Index
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last updated on 2024-10-23 21:22 CEST by the dblp team
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