Gideon Mekonnen Jonathan, a member of the Digital Transformation research group, has received best paper award for the papers presented at the Annual Conference of the Midwest Association for Information Systems(MWAIS) and the ACM SIGMIS Computers and People Research 2024. For more information see the link: https://www.linkedin.com/posts/gideonmekonnen_awards-workforceagility-digitaltransformation-activity-7247694291463004160-vmIW?utm_source=share&utm_medium=member_desktop.
Early sepsis detection – Best paper award – ICTAI 2022
The 34th IEEE International Conference on Tools with Artificial Intelligence was held virtually from 31s of October to the 2nd of November. With Aron Henriksson and in collaboration with Karolinska Institutet we presented our paper “Improving the Timeliness of Early Prediction Models for Sepsis through Utility Optimization” and we are very happy to announce that we received the best paper award. In the paper that will be published in the proceedings of the conference, we explore the capabilities of using custom objective functions to develop a machine learning model that can perform sepsis prediction over time in a manner that will be useful for practitioners in assisting them to perform timely intervention and initiate treatment early, which is key to survival.
PhD Student Mahbub Ul Alam Received the Best Student Paper Award at the IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS 2022)
Hello Everyone,
Greetings. I hope you are well. I would like to share some very good news with you.
I recently published a paper with two other co-authors at the IEEE 35th International Symposium on Computer Based Medical Systems (CBMS 2022, July 21-23, 2022, Shenzhen, China, Online Event). CBMS is the premier conference for computer-based medical systems, and one of the main conferences within the fields of medical informatics and biomedical informatics.
The title of my paper is “Exploring LRP and Grad-CAM visualization to interpret multi-label-multi-class pathology prediction using chest radiography“, (Mahbub Ul Alam, Jón Rúnar Baldvinsson and Yuxia Wang)”. In this paper, we tried to explain the decision process of deep neural networks to predict pathology (abnormality) in chest-X ray data using two popular interpretable methods. We investigated whether this explanation matches the clinical diagnosis or not. Interpretability is very crucial and it is emphasized in the recent European Union Artifical Intelligence Act. We hope that this paper will create a positive impact in this aspect.
The paper was received well during the CBMS 2022 symposium presentation time. I am delighted to inform you that the paper received the ‘best student paper award’. The award was provided by the IEEE Technical Committee on Computational Life Science (TCCLS).
I am very honoured and would like to thank DSV for providing me with this opportunity. I am fortunate to be working here to get a second award for my research work. Previously I won the ‘best paper award’ at BIOSTEC HEALTHINF 2020 (you can read more about it here).
Want to know more about the paper? Please check out the following presentation video I made!
Abstract:
The area of interpretable deep neural networks has received increased attention in recent years due to the need for transparency in various fields, including medicine, healthcare, stock market analysis, compliance with legislation, and law. Layer-wise Relevance Propagation (LRP) and Gradient-weighted Class Activation Mapping (Grad-CAM) are two widely used algorithms to interpret deep neural networks. In this work, we investigated the applicability of these two algorithms in the sensitive application area of interpreting chest radiography images. In order to get a more nuanced and balanced outcome, we use a multi-label classification-based dataset and analyze the model prediction by visualizing the outcome of LRP and Grad-CAM on the chest radiography images. The results show that LRP provides more granular heatmaps than Grad-CAM when applied to the CheXpert dataset classification model. We posit that this is due to the inherent construction difference of these algorithms (LRP is layer-wise accumulation, whereas Grad-CAM focuses primarily on the final sections in the model’s architecture). Both can be useful for understanding the classification from a micro or macro level to get a superior and interpretable clinical decision support system.
Distinguished Member of Association for Information Systems
I am very happy and proud that Association for Information Systems (AIS) member program has recognized my activity to have a significant impact on the association and made me a Distinguished Member of AIS (https://aisnet.org/page/DistinguishedMemberList).
Paper published in AMCIS 2021 Proceedings is among the Most Popular Papers
The results of the research work done by Rahmat Mulyana, Lazar Rusu and Erik Perjons (all members of research group in IT Management and Governance at DSV) in IT Governance and Digital Transformation areas has raised the interest of the worldwide IS community, like is the the Americas Conference on Information Systems (AMCIS) conference, that is a top conference in IS area. Their paper entitled IT Governance Mechanisms Influence on Digital Transformation: A Systematic Literature Review published in AMCIS 2021 Proceedings is mentioned among the Most Popular Papers at AMCIS 2021 (https://aisel.aisnet.org/amcis2021/topdownloads.html).
2020 IBM Academic Award
Professor Lazar Rusu at Stockholm University has received in 2020 the IBM Academic Award for the research project entitled “Risks in Cloud Computing Relationships in Public Organizations”. The project aims to identify the risk factors in cloud computing relationships in public organizations and how to mitigate these risks.
Best Theoretical Paper Award at 17th European, Mediterranean & Middle Eastern Conference on Information Systems (EMCIS 2020)
The paper entitled “The Influence of Cloud Computing on IT Governance in a Swedish Municipality” (authors: Parisa Aasi, Jovana Nikic, Melisa Li, Lazar Rusu) presented at 17th European, Mediterranean & Middle Eastern Conference on Information Systems (EMCIS 2020) has received the “Best Theoretical Paper Award”.
Outstanding Reviewer Award Winners at Americas Conference on Information Systems (AMCIS 2020)
Americas Conference on Information Systems (AMCIS) is one of the leading conferences in Information Systems area (https://aisnet.org/page/AMCISPage) that in 2020 was held as a virtual conference (https://amcis2020.aisconferences.org/).
In this year, I have served AMCIS 2020 as mini-track chair and as session chair of “IT Governance and Business-IT Alignment in the Era of Digital Transformation”, and the mini-track I was chairing has be the one that has received the most papers in the Strategic and Competitive Uses of IT track (https://amcis2020.aisconferences.org/track-descriptions/#toggle-id-24).
Furthermore, I am very happy and proud that at AMCIS 2020, I have been among the Outstanding Reviewer Award Winners at AMCIS 2020, and also nominated as the best reviewer at Strategic and Competitive Uses of IT track at AMCIS 2020 (2020 AMCIS SCUIT Track Session CHAIRS FINAL).
A screenshot taken from the video of the AMCIS 2020 Awards Ceremony with some of the Outstanding Reviewer Award Winners is included below.
