Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Engineering, Other, Docent in Computational Health Technologies, Tampere University
Award Date: 30 Jun 2025
Engineering, Doctorate, PhD in Computer Engineering, Başkent University
Award Date: 1 Jun 2020
Engineering, Master, Master's in Computer Engineering, Başkent University
Award Date: 1 Jul 2015
Engineering, Bachelor, Bachelor's Degree in Computer Engineering, TOBB University of Economics and Technology
Award Date: 2 Dec 2013
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 1 Active
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PHASE IV AI: Privacy compliant health data as a service for AI development
Pajula, J. (Manager), Asuroglu, T. (Participant), Pölönen, H. (Participant), Degerli Ahishali, A. (Participant), Lähteenmäki, J. (Participant), Merilinna, J. (Participant) & El Mekkaoui, K. (Participant)
1/10/23 → 30/09/26
Project: EU project
Research output
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A comparative feature selection study: Predicting Alzheimer's disease using primary healthcare and social services data
Sourkatti, H., Asuroglu, T., Itkonen, M., Alahäivälä, A.-L. I., Tolppanen, A.-M., Ihalainen, J. & Forsberg, M. M., Oct 2025, In: Informatics in Medicine Unlocked. 59, 101703.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access -
A deep learning approach for sepsis monitoring via severity score estimation
Aşuroğlu, T. & Oğul, H., Jan 2021, In: Computer Methods and Programs in Biomedicine. 198, 105816.Research output: Contribution to journal › Article › Scientific › peer-review
50 Citations (Scopus) -
Using Machine Learning Methods to Predict the Lactate Trend of Sepsis Patients in the ICU
Arslantas, M. K., Asuroglu, T., Arslantas, R., Pashazade, E., Dincer, P. C., Altun, G. T. & Kararmaz, A., 5 May 2024, Digital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7–8, 2024, Proceedings, Part I. Springer, p. 3-16 (Communications in Computer and Information Science, Vol. 2084).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Open Access2 Citations (Scopus) -
Parkinson's disease monitoring from gait analysis via foot-worn sensors
Aşuroğlu, T., Açıcı, K., Berke Erdaş, Ç., Kılınç Toprak, M., Erdem, H. & Oğul, H., 1 Jan 2018, In: Biocybernetics and Biomedical Engineering. 38, 3, p. 760-772Research output: Contribution to journal › Article › Scientific › peer-review
71 Citations (Scopus) -
A deep learning approach for parkinson’s disease severity assessment
Aşuroğlu, T. & Oğul, H., Sept 2022, In: Health and Technology. 12, 5, p. 943–953Research output: Contribution to journal › Article › Scientific › peer-review
Open Access51 Citations (Scopus)