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Wavy Abstract Background

(The ones that are not Trade Secrets)


Detection of mild cognitive impairment based on mouse movement data of trail making test

Dr. Gergely Hanczar, Dr. Erika Griechisch, Nora Ovad, Oliver Mate Torteli, Gabor Toth, David Hanak, Balazs Vertes, Dr. Andras Horvath & Prof. Dr. Anita Kamondi

Hanczár, G., Stippinger, M., Hanak, D., Kurbucz, T. M., Torteli, M. O., Chripko, A. & Somogyvari, Z (2023). Feature space reduction method for ultrahigh-dimensional, multiclass data: random forest-based multiround screening (RFMS). Machine Learning: Science and Technology, 4, 045012.

Hanczár, G., Griechisch, E., Ovád, N., Törteli, O. M., Tóth, G., Hanák, D., Vértes, B., Horváth, A., & Kamondi, A. (2022). Detection of mild cognitive impairment based on mouse movement data of trail making test. Informatics in Medicine Unlocked, 35, 101120.

Hanczár, G., Griechisch, E., Molnár, Á., & Tóth, G. (2022). Motor Movement Data Collection from Older People with Tablets and Digital Pen-Based Input Devices. In: Carmona-Duarte, C., Diaz, M., Ferrer, M.A., Morales, A. (eds) Intertwining Graphonomics with Human Movements. IGS 2022. Lecture Notes in Computer Science, vol 13424. Springer, Cham.

Stippinger, M., Hanák, D., Kurbucz, M. T., Hanczár, G., Törteli, O. M., & Somogyvári, Z. (2023). BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space. SoftwareX, 22, 101366.

Griechisch, E., Ward, J. R., & Hanczár, G. (2019). Anomalies in measuring speed and other dynamic properties with touchscreens and tablets. 2019 International Conference of the Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, pp. 1-6.

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