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Persoonlijk profiel

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.

Vingerafdruk Verdiep u in de onderzoeksgebieden waarop Tom H.G.F. Bakkes actief is. Deze onderwerplabels komen uit het werk van deze persoon. Samen vormen ze een unieke vingerafdruk.

  • 5 Soortgelijke profielen

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Onderzoeksoutput

  • 1 Citaties
  • 2 Conferentiebijdrage
  • 1 Poster
  • 1 Tijdschriftartikel

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, blz. 2161-2164 4 blz. 8857374

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer 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., okt 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. Piscataway: IEEE Computer Society, blz. 1141-1144 4 blz. 8926228

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

  • Open Access
    Bestand
  • 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 blz., 2449.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
    Bestand
  • 1 Citaat (Scopus)
    98 Downloads (Pure)

    Scriptie

    Machine learning for classification of uterine activity during IVF cycles

    Auteur: Bakkes, T., 13 dec 2018

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

    Scriptie/masterproef: Master