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- Hamesse, CharlesKTH,Royal Military Academy, Brussels, Belgium (author)
Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation
- Article/chapterEnglish2019
Publisher, publication year, extent ...
- ML Research Press,2019
- electronicrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:kth-258070
- https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-258070URI
- https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-350359URI
Supplementary language notes
- Language:English
- Summary in:English
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- SwePubSwePub
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Notes
- Not duplicate with DiVA 1261619QC 20190912
- QC 20240715
- Achilles Tendon Rupture (ATR) is one of the typical soft tissue injuries. Rehabilitation after such a musculoskeletal injury remains a prolonged process with a very variable outcome. Accurately predicting rehabilitation outcome is crucial for treatment decision support. However, it is challenging to train an automatic method for predicting the AT Rrehabilitation outcome from treatment data, due to a massive amount of missing entries in the data recorded from ATR patients, as well as complex nonlinear relations between measurements and outcomes. In this work, we design an end-to-end probabilistic framework to impute missing data entries and predict rehabilitation outcomes simultaneously. We evaluate our model on a real-life ATR clinical cohort, comparing with various baselines. The proposed method demonstrates its clear superiority over traditional methods which typically perform imputation and prediction in two separate stages.
Subject headings and genre
- NATURVETENSKAP Data- och informationsvetenskap Datavetenskap hsv//swe
- NATURAL SCIENCES Computer and Information Sciences Computer Sciences hsv//eng
- TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik hsv//swe
- ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering hsv//eng
Added entries (persons, corporate bodies, meetings, titles ...)
- Tu, RuiboKTH,Robotik, perception och lärande, RPL(Swepub:kth)u14aw83f (author)
- Ackermann, PaulKarolinska University Hospital, Stockholm, Sweden (author)
- Kjellström, Hedvig,1973-KTH,Robotik, perception och lärande, RPL(Swepub:kth)u1izkbhh (author)
- Zhang, ChengMicrosoft Research, Cambridge, UK (author)
- KTHRoyal Military Academy, Brussels, Belgium (creator_code:org_t)
Related titles
- In:Proceedings of Machine Learning Research 106: ML Research Press, s. 614-640
- In:Proceedings of the 4th Machine Learning for Healthcare Conference, MLHC 2019: ML Research Press, s. 614-640
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