If you made any changes in Pure these will be visible here soon.

Personal profile

Academic background

Tom Bakkes received his bachelor’s degree in Electrical Engineering in 2016. He continued his studies in Electrical Engineering for his master’s degree and specialized in the signals processing systems group. This is where he got interested in using the techniques he had learned in a Care & Cure setting. For his graduation project he joined the Biomedical Diagnostics lab where he worked on using machine learning for predicting the outcome of in-vitro fertilization treatments. Following that he received his master’s degree in 2018 and has now continued working in the Biomedical Diagnostics lab as a PhD candidate focusing on clinical decision support systems in perioperative care.

Research profile

Tom Bakkes is a PhD candidate in the Biomedical Diagnostics lab at the Eindhoven University of Technology. Here he works on using statistics and machine learning to build clinical decision support systems for the perioperative care. Thereby his current studies focus on automatic detection of patient-ventilation asynchrony, and early detection of deterioration in post-operative patients. For the latter study he works in close collaboration with clinical experts from the Catharina hospital in Eindhoven.

Quote

I work on clinical decision support systems in the perioperative care that will allow clinicians to achieve a more accurate and faster insight on their patients.

Fingerprint Dive into the research topics where Tom H.G.F. Bakkes is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 5 Similar Profiles

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output

  • 1 Citations
  • 2 Conference contribution
  • 1 Poster
  • 1 Article

Machine learning for classification of uterine activity outside pregnancy

Bakkes, T. H. G. F., Sammali, F., Kuijsters, N. P. M., Turco, S., Rabotti, C., Schoot, D. & Mischi, M., Jul 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Piscataway: Institute of Electrical and Electronics Engineers, p. 2161-2164 4 p. 8857374

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • 3 Downloads (Pure)

    Prediction of embryo implantation by machine learning based on ultrasound strain imaging

    Sammali, F., Blank, C., Bakkes, T. H. G. F., Huang, Y., Rabotti, C., Schoot, B. C. & Mischi, M., Oct 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. Piscataway: IEEE Computer Society, p. 1141-1144 4 p. 8926228

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • Open Access
    File
  • Unobtrusive respiratory flow monitoring using a thermopile array: a feasibility study

    Lorato, I., Bakkes, T., Stuijk, S., Meftah, M. & de Haan, G., 15 Jun 2019, In : Applied Sciences. 9, 12, 15 p., 2449.

    Research output: Contribution to journalArticleAcademicpeer-review

    Open Access
    File
  • 1 Citation (Scopus)
    98 Downloads (Pure)

    Student theses

    Machine learning for classification of uterine activity during IVF cycles

    Author: Bakkes, T., 13 Dec 2018

    Supervisor: Mischi, M. (Supervisor 1), Sammali, F. (Supervisor 2) & Schoot, B. (Supervisor 2)

    Student thesis: Master