prof. dr. ir. Sofie Van Hoecke

Faculty of Engineering and Architecture > Department of Electronics and information systems

ORCID iD: 0000-0002-7865-6793
Bio (via ORCID): I graduated from the Engineering Department from the Ghent University in 2003. Following up on my studies in computer science, I achieved a PhD in computer science engineering at the Department of Information Technology at the same university. After being a postdoctoral research engineer at the Department of Information Technology, I started as lecturer ICT and ICT research coordinator at the University College West-Flanders. Since 2013, I joined Ghent University again. Currently, I am associate professor at IDLab, Ghent University-imec and my research focuses on machine learning and hybrid machine learning for predictive maintenance and predictive healthcare.

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- Journal Article
- A1
- open access
An artificial intelligence-powered digital pathology platform to support large-scale deworming programs against soil-transmitted helminthiasis and intestinal schistosomiasis in resource-limited settings

Peter K. Ward, Mohammed Aliy Mohammed (UGent) , Mio Ayana Heda, Lindsay A. Broadfield, Peter Dahlberg, Daniel Dana, Gemechu Tadesse Leta, Zeleke Mekonnen Kurmane (UGent) , Betty Nabatte, Narcis Kabatereine, et al.

(2026) PLOS NEGLECTED TROPICAL DISEASES. 20(3).
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Mobile technology for just-in-time prediction of depression : a scoping review

Yannick Vander Zwalmen (UGent) , Matthias Maerevoet (UGent) , Tina Coenen (UGent) , Kristof Hoorelbeke (UGent) , Stephanie Chen (UGent) , Mathias De Brouwer (UGent) , Marie-Anne Vanderhasselt (UGent) , Sofie Van Hoecke (UGent) , Klaas Bombeke (UGent) , Rudi De Raedt (UGent) , et al.

(2026) NATURE MENTAL HEALTH.
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Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction

Jef Jonkers (UGent) , Frank Coopman (UGent) , Luc Duchateau (UGent) , Glenn Van Wallendael (UGent) and Sofie Van Hoecke (UGent)

(2026) MEDICAL IMAGE ANALYSIS. 110.
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Cardiac vagal tone is associated with physical activity but not with depressive symptoms, work stress, and social support : a large‐scale 10‐year follow‐up study

Zefeng Li (UGent) , Stephanie Chen (UGent) , Ernst Rietzschel (UGent) , Gosia Kozusznik (UGent) , Sofie Van Hoecke (UGent) , Marie-Anne Vanderhasselt (UGent) and Matias Miguel Pulópulos Tripiana (UGent)

(2026) APPLIED PSYCHOLOGY-HEALTH AND WELL BEING. 18(1).
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Toward context-aware anomaly detection for AIOps in microservices using dynamic knowledge graphs

Pieter Moens (UGent) , Bram Steenwinckel (UGent) , Femke Ongenae (UGent) , Bruno Volckaert (UGent) and Sofie Van Hoecke (UGent)

(2026) IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT. 23. p.1970-1988
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Using machine learning to predict patient-reported symptom clusters in prostate cancer patients receiving radiotherapy

Elke Rammant (UGent) , Emile Deman (UGent) , Valerie Fonteyne (UGent) , Lindsay Poppe (UGent) , Renée Bultijnck (UGent) , Piet Dirix, Gert De Meerleer, Karin Haustermans, Ann Van Hecke (UGent) , Miguel E. Aguado-Barrera, et al.

(2026) HEALTH AND QUALITY OF LIFE OUTCOMES. 24(1).
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Improved IOL power calculation with femtosecond laser enhanced refractive outcome prediction

Jeroen Van Der Donckt (UGent) , Joshua A. Young, Michaël Rademaker (UGent) , Saurabh Menon, Chin-Wen Chang, Gilles Vandewiele (UGent) , Benjamin Straker, David Dewey, George Dai, Javier Gonzalez, et al.

(2025) TRANSLATIONAL VISION SCIENCE & TECHNOLOGY. 14(11).
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Towards trustful machine learning for antimicrobial therapy using an explainable artificial intelligence dashboard

Thomas De Corte (UGent) , Jarne Verhaeghe (UGent) , Femke Ongenae (UGent) , Jan De Waele (UGent) and Sofie Van Hoecke (UGent)

(2025) APPLIED SCIENCES-BASEL. 15(20).
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Impact of window sizes and sensor quality on MCSA for misalignment fault detection

Colin Soete (UGent) , Jeroen Van Der Donckt (UGent) , Nathan Vandemoortele (UGent) , Michaël Rademaker (UGent) and Sofie Van Hoecke (UGent)

(2025) INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY. 141(12). p.6179-6194
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Requirements and concerns of individuals remitted from depression for an early relapse detection mHealth app : focus group study

Tina Coenen (UGent) , Matthias Maerevoet (UGent) , Stephanie Chen (UGent) , Mathias De Brouwer (UGent) , Sofie Van Hoecke (UGent) , Ernst Koster (UGent) , Mariek Vanden Abeele (UGent) and Klaas Bombeke (UGent)

(2025) JMIR MHEALTH AND UHEALTH. 13.

Academic Bibliography

prof. dr. ir. Sofie Van Hoecke

An artificial intelligence-powered digital pathology platform to support large-scale deworming programs against soil-transmitted helminthiasis and intestinal schistosomiasis in resource-limited settings

Mobile technology for just-in-time prediction of depression : a scoping review

Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction

Cardiac vagal tone is associated with physical activity but not with depressive symptoms, work stress, and social support : a large‐scale 10‐year follow‐up study

Toward context-aware anomaly detection for AIOps in microservices using dynamic knowledge graphs

Using machine learning to predict patient-reported symptom clusters in prostate cancer patients receiving radiotherapy

Improved IOL power calculation with femtosecond laser enhanced refractive outcome prediction

Towards trustful machine learning for antimicrobial therapy using an explainable artificial intelligence dashboard

Impact of window sizes and sensor quality on MCSA for misalignment fault detection

Requirements and concerns of individuals remitted from depression for an early relapse detection mHealth app : focus group study

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