| 1. |
- Brännvall, Rickard, 1975-, et al.
(författare)
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Homomorphic encryption enables private data sharing for digital health : Winning entry to the Vinnova innovation competition Vinter 2021-22
- 2022
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Ingår i: 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665471268
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Konferensbidrag (refereegranskat)abstract
- People living with type 1 diabetes often use several apps and devices that help them collect and analyse data for a better monitoring and management of their disease. When such health related data is analysed in the cloud, one must always carefully consider privacy protection and adhere to laws regulating the use of personal data. In this paper we present our experience at the pilot Vinter competition 2021-22 organised by Vinnova. The competition focused on digital services that handle sensitive diabetes related data. The architecture that we proposed for the competition is discussed in the context of a hypothetical cloud-based service that calculates diabetes self-care metrics under strong privacy preservation. It is based on Fully Homomorphic Encryption (FHE)-a technology that makes computation on encrypted data possible. Our solution promotes safe key management and data life-cycle control. Our benchmarking experiment demonstrates execution times that scale well for the implementation of personalised health services. We argue that this technology has great potentials for AI-based health applications and opens up new markets for third-party providers of such services, and will ultimately promote patient health and a trustworthy digital society.
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| 2. |
- Danielsson, Benjamin, et al.
(författare)
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Classifying Implant-Bearing Patients via their Medical Histories : a Pre-Study on Swedish EMRs with Semi-Supervised GAN-BERT
- 2022
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Ingår i: 2022 Language Resources and Evaluation Conference, LREC 2022. - : European Language Resources Association (ELRA). - 9791095546726 ; , s. 5428-5435
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Konferensbidrag (refereegranskat)abstract
- In this paper, we compare the performance of two BERT-based text classifiers whose task is to classify patients (more precisely, their medical histories) as having or not having implant(s) in their body. One classifier is a fully-supervised BERT classifier. The other one is a semi-supervised GAN-BERT classifier. Both models are compared against a fully-supervised SVM classifier. Since fully-supervised classification is expensive in terms of data annotation, with the experiments presented in this paper, we investigate whether we can achieve a competitive performance with a semi-supervised classifier based only on a small amount of annotated data. Results are promising and show that the semi-supervised classifier has a competitive performance when compared with the fully-supervised classifier. © licensed under CC-BY-NC-4.0.
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| 3. |
- Rennes, Evelina, 1990-, et al.
(författare)
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The Swedish Simplification Toolkit : Designed with Target Audiences in Mind
- 2022
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Ingår i: 2nd Workshop on Tools and Resources for REAding DIfficulties, READI 2022 - collocated with the International Conference on Language Resources and Evaluation Conference, LREC 2022. - : European Language Resources Association (ELRA). - 9791095546849 ; , s. 31-38
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present the current version of The Swedish Simplification Toolkit. The toolkit includes computational and empirical tools that have been developed along the years to explore a still neglected area of NLP, namely the simplification of “standard” texts to meet the needs of target audiences. Target audiences, such as people affected by dyslexia, aphasia, autism, but also children and second language learners, require different types of text simplification and adaptation. For example, while individuals with aphasia have difficulties in reading compounds (such as arbetsmarknadsdepartement, eng. ministry of employment), second language learners struggle with cultural-specific vocabulary (e.g. konflikträdd, eng. afraid of conflicts). The toolkit allows user to selectively select the types of simplification that meet the specific needs of the target audience they belong to. The Swedish Simplification Toolkit is one of the first attempts to overcome the one-fits-all approach that is still dominant in Automatic Text Simplification, and proposes a set of computational methods that, used individually or in combination, may help individuals reduce reading (and writing) difficulties.
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