Research output per year
Research output per year
Jannik Skyttegaard Pedersen, Martin Sundahl Laursen, Pernille Just Vinholt, Anne Bryde Alnor, Thiusius Rajeeth Savarimuthu
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Clinical machine learning algorithms have shown promising results and could potentially be implemented in clinical practice to provide diagnosis support and improve patient treatment. Barriers for realisation of the algorithms’ full potential include bias which is systematic and unfair discrimination against certain individuals in favor of others. The objective of this work is to measure anatomical bias in clinical text algorithms. We define anatomical bias as unfair algorithmic outcomes against patients with medical conditions in specific anatomical locations. We measure the degree of anatomical bias across two machine learning models and two Danish clinical text classification tasks, and find that clinical text algorithms are highly prone to anatomical bias. We argue that datasets for creating clinical text algorithms should be curated carefully to isolate the effect of anatomical location in order to avoid bias against patient subgroups.
Original language | English |
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Title of host publication | Findings of the Association for Computational Linguistics: EACL 2023 |
Publisher | Association for Computational Linguistics (ACL) |
Publication date | 2023 |
Pages | 1368-1380 |
ISBN (Electronic) | 9781959429470 |
Publication status | Published - 2023 |
Event | 17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023 - Findings of EACL 2023 - Dubrovnik, Croatia Duration: 2. May 2023 → 6. May 2023 |
Conference | 17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023 - Findings of EACL 2023 |
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Country/Territory | Croatia |
City | Dubrovnik |
Period | 02/05/2023 → 06/05/2023 |
Sponsor | Adobe, Babelscape, Bloomberg Engineering, Duolingo, LivePerson |
Research output: Thesis › Ph.D. thesis