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News and Events

Papers published and accepted for publication in Proceedings of Pacific Asia Conference on Information Systems (PACIS) 2022, Americas Conference on Information Systems (AMCIS) 2022, and International Conference on Information Systems Development (ISD) 2022  

IT Management, SYSLAB

A paper written by Rahmat Mulyana, Lazar Rusu, and Erik Perjons and entitled: “IT Governance Mechanisms that Influence Digital Transformation: A Delphi Study in Indonesian Banking and Insurance” has been published in PACIS 2022 Proceedings, Paper 267, Association for Information Systems (Nominated for the Best Paper (Paper 1160) in PACIS 2022 Detailed Program: https://pacis2022.aisconferences.org/schedule-program/conference-program/)

A paper written by Parisa Aasi, Sebastian Atug, Lorenzo  Cermeno, and Lazar Rusu, and entitled: “Digital Transformation Success Through Aligning the Organizational Structure: Case Study of Swedish Public Organizations” has been accepted for publication in AMCIS 2022 Proceedings, Association for Information Systems

A paper written by Gideon Mekonnen Jonathan, Lazar Rusu, and Erik Perjons and entitled: “Digital Transformation in Public Organisations: IT Alignment-Related Success Factors” has been accepted for publication in ISD 2022 Proceedings, Association for Information Systems

Paper at ACL 2022 workshop: BioNLP

Health Informatics, Information Systems, Publication, Research Paper, SYSLAB

I had the pleasure of presenting a poster of a paper by Hercules Dalianis and me: Utility Preservation of Clinical Text After De-Identification. The paper investigates how automatic de-identification, a necessarily imperfect process, impacts the quality of the resulting texts. When a de-identification system incorrectly class a word as sensitive, the data will be slightly corrupted. Many researchers have been worried that this would make the data less useful, and we investigate this issue.

The impact of automatic de-identification on quality is evaluated using both qualitative and quantitative (machine learning) methods. We find no losses in utility for clinical NLP on three downstream clinical tasks. In fact, the machine learning models trained using automatic de-identification seem to work just as well as those trained using sensitive data. We also find that the experts in our study think the de-identification works well.

Participating in the 60th ACL conference was a great experience. I learned a lot from our global NLP community and met many researchers interested in our work at DSV. You can find the paper here, and the poster I presented here.

LREC 2022 – Accepted papers

Health Informatics, Publication, Research Paper, SYSLAB

Hello everyone!

We have two new papers accepted to the 13th Language Resources and Evaluation Conference, LREC 2022 that takes place in Marseille the upcoming June!

The first paper is authored by Thomas Vakili, Aron Henriksson, Hercules Dalianis, and me and is called “Downstream Task Performance of BERT Models Pre-Trained Using Automatically De-Identified Clinical Data” with code 412. It evaluates the performance of a language model that is trained using De-identified clinical text in later tasks, and explores the de-identification impact in the development of the language model.

The second paper is authored by Aron Henriksson, Hercules Dalianis, and me and is called “Evaluating Pre-training Strategies for Clinical BERT Models” with code 661. It empirically compares different pre-training strategies for the development of domain-adapted language models in the Swedish clinical text domain.

You can find all the accepted papers including the ones mentioned above here!

 

 

Ph.D. Funding for Research in IT Management and Governance from Swedish Research School of Management and Information Technology (MIT)

IT Management, New Project, SYSLAB

The application submitted in this year to Swedish Research School of Management and Information Technology (MIT) for Ph.D. funding for research in IT management and governance at DSV/Stockholm University has been successfully. In the next five years DSV will receive 1.750.000 SEK from MIT for co-financing a Ph.D. position in IT management and governance. For more information about Swedish Research School of Management and Information Technology (MIT) please access the following link: http://www.mit.uu.se/

AAAI Fall Symposium and EMNLP – November 2021

Health Informatics, Presentation, Publication, Research Paper, SYSLAB, Visit

Professor Hercules Dalianis and I got a paper about the privacy preserving qualities of BERT accepted to the AAAI Fall Symposium on Human Partnership with Medical Artificial Intelligence! The paper is titled Are Clinical BERT Models Privacy Preserving? The Difficulty of Extracting Patient-Condition Associations. Our results strongly suggest that BERT’s poor generative capabilities makes it resistant to training data extraction attacks. Other models, such as GPT-2, have been shown to be susceptible to these attacks. From a privacy perspective, being a poor generator may be a feature!

Later in the same week, I flew from Stockholm to Punta Cana in the Dominican Republic to participate at EMNLP 2021. Almost 500 participants were there, with the total number of participants exceeding 4,000. There were many interesting presentations regarding NLP in general, but also some that were specifically about the privacy aspects of NLP. It was a great experience to learn where the field is headed and also to get to know many talented researchers. I have written a summary of some of the interesting papers – reach out if you are interested in it.

DSV at the First ClinCode Conference in Tromsø, Norway

Health Informatics, Presentation, SYSLAB, Visit

Professor Hercules Dalianis, Sonja Remmer and myself represented DSV at the First ClinCode Conference. The conference gathered experts in medicine and computer science from across the Nordics and took place at the University Hospital of North Norway (UNN) in Tromsø.

The conference was chaired by Hercules, who is also a guest professor at the Norwegian Centre for E-health Research. Sonja shared her work on automatic ICD-10 classification using BERT and I spoke about the difficulty of extracting training data from clinical BERT models.

Several participants had an industry or medical background. This provided valuable insights into how our research at DSV may be used in practice and what challenges are most important. It also highlighted the great potential that can be unlocked by continuing to investigate ICD-10 classification and other medical NLP problems.

Many excellent ideas were hatched in the discussions, and it was lovely to visit the beautiful polar city of Tromsø. Personally, I really look forward to future iterations of the conference!

Press release

Three papers accepted to the International Conference Recent Advances in Natural Language Processing, RANLP 2021, September 1-3, 2021, Bulgaria.

Health Informatics, Publication, Research Paper, SYSLAB

Three papers accepted to the International Conference Recent Advances in Natural Language Processing, RANLP 2021, September 1-3, 2021 in Varna, Bulgaria,
from the Clinical Text Mining group at DSV: 

Sonja Remmer, Anastasios Lamproudis and Hercules Dalianis.
Multi-label Diagnosis Classification of Swedish Discharge Summaries – ICD-10 Code Assignment Using KB-BERT. 

Alberto Blanco, Sonja Remmer, Alicia Pérez, Hercules Dalianis and Arantza Casillas.
On the contribution of per-ICD attention mechanisms to classify health records in languages with fewer resources than English. 

Anastasios Lamproudis, Aron Henriksson and Hercules Dalianis. 
Developing a Clinical Language Model for Swedish: Continued Pretraining of Generic BERT with In-Domain Data. 

The first paper in collaboration with the Norwegian Centre for E-health Research in Tromsø. Norway and the second paper also with the HiTZ Center – Ixa, University of the Basque Country UPV/EHU, Donostia, Spain.

The two first papers study how to automatically assign ICD-10 diagnosis codes to a discharge summary, for Swedish and for Spanish a respectively. Usually this time consuming work is carried out manually by a physician or a coder.We use machine learning and specifically Deep AI Learning to perform this and already manually assign codes to discharges summaries.

In the third paper is constructed a clinical deep learning BERT model for Swedish that performs much better than a regular non-clinical model for clinical down stream tasks as for example automatic ICD-10 diagnosis coding.