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2020 – today
- 2024
[j4]Emilia Ståhlbom
, Jesper Molin, Anders Ynnerman, Claes Lundström:
Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data. Comput. Graph. Forum 43(3) (2024)- 2023
- [j3]Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström:
The thorny complexities of visualization research for clinical settings: A case study from genomics. Frontiers Bioinform. 3 (2023) - 2022
- [c7]Emilia Ståhlbom, Jesper Molin, Claes Lundström, Anders Ynnerman:
Visualization Challenges of Variant Interpretation in Multiscale NGS Data. EuroVis (Posters) 2022: 107-109 - 2021
- [c6]Freja Fagerblom, Karin Stacke, Jesper Molin:
Combatting out-of-distribution errors using model-agnostic meta-learning for digital pathology. Medical Imaging: Digital Pathology 2021 - 2020
- [c5]Martin Lindvall, Jesper Molin:
Verification Staircase: a Design Strategy for Actionable Explanations. ExSS-ATEC@IUI 2020 - [i3]Martin Lindvall, Jesper Molin:
Designing for the Long Tail of Machine Learning. CoRR abs/2001.07455 (2020)
2010 – 2019
- 2018
- [j2]Henning Höfener, André Homeyer, Nick Weiss, Jesper Molin, Claes F. Lundström, Horst K. Hahn:
Deep learning nuclei detection: A simple approach can deliver state-of-the-art results. Comput. Medical Imaging Graph. 70: 43-52 (2018) - [j1]Martin Lindvall, Jesper Molin, Jonas Löwgren:
From machine learning to machine teaching: the importance of UX. Interactions 25(6): 52-57 (2018) - [c4]Martin Lindvall, Jesper Molin, Jonas Löwgren:
The Importance of UX for Machine Teaching. AAAI Spring Symposia 2018 - [i2]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir M. Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. CoRR abs/1807.08284 (2018) - 2016
- [b1]Jesper Molin:
Diagnostic Review with Digital Pathology: Design of digitals tools for routine diagnostic use. Chalmers University of Technology, Gothenburg, Sweden, 2016 - [c3]Hanna Källén, Jesper Molin, Anders Heyden, Claes Lundström, Kalle Åström:
Towards grading gleason score using generically trained deep convolutional neural networks. ISBI 2016: 1163-1167 - [c2]Jesper Molin, Pawel W. Wozniak, Claes Lundström, Darren Treanor, Morten Fjeld:
Understanding Design for Automated Image Analysis in Digital Pathology. NordiCHI 2016: 58 - [i1]Jesper Molin, Anna Bodén, Darren Treanor, Morten Fjeld, Claes Lundström:
Scale Stain: Multi-Resolution Feature Enhancement in Pathology Visualization. CoRR abs/1610.04141 (2016) - 2014
- [c1]Jesper Molin, Kavitha Shaga Devan, Karin Wårdell, Claes Lundström:
Feature-enhancing zoom to facilitate Ki-67 hot spot detection. Medical Imaging: Digital Pathology 2014: 90410W
Coauthor Index
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