Synchrotron and Neutron Tomography of Paleontological Objects on the Facilities of the Kurchatov Institute. - Alexey Pakhnevich; Andrey Kurkin; Alexander Lavrov; Konstantin Tarasenko; Ekaterina Kovalenko; Alexander Kaloyan; Konstantin Podurets (J. Imaging, 2018)

Data-Driven Analysis of Parkinson's Disease and its Detection at an Early Stage. - Aleksandr Talitckii; Anna Anikina; Ekaterina Kovalenko; Oscar Mayora; Venet Osmani; Olga Zimniakova; Maxim Semenov; Ekaterina Bril; Dmitry V. Dylov; Andrey Somov (PervasiveHealth, 2020)

Neutron and Synchrotron Imaging Studies of Preservation State of Metal of Cultural Heritage Objects. - Ekaterina Kovalenko; Mikhail Murashev; Konstantin Podurets; Elena Tereschenko; Ekaterina Yatsishina (J. Imaging, 2021)

Defining Optimal Exercises for Efficient Detection of Parkinson's Disease Using Machine Learning and Wearable Sensors. - Aleksandr Talitckii; Anna Anikina; Ekaterina Kovalenko; Aleksei Shcherbak; Oscar Mayora; Olga Zimniakova; Ekaterina Bril; Maxim Semenov; Dmitry V. Dylov; Andrey Somov (IEEE Trans. Instrum. Meas., 2021)

Comparative Study of Wearable Sensors, Video, and Handwriting to Detect Parkinson's Disease. - Aleksandr Talitckii; Ekaterina Kovalenko; Aleksei Shcherbak; Anna Anikina; Ekaterina Bril; Olga Zimniakova; Maxim Semenov; Dmitry V. Dylov; Andrey Somov (IEEE Trans. Instrum. Meas., 2022)

Dominant Hand Invariant Parkinson's Disease Detection Using 1-D CNN Model and STFT-based IMU Data Fusion. - Aleksei Shcherbak; Ekaterina Kovalenko; Ekaterina Bril; Anna Baldycheva; Andrey Somov (ISIE, 2023)

Detection and Classification of Early Stages of Parkinson's Disease Through Wearable Sensors and Machine Learning. - Aleksei Shcherbak; Ekaterina Kovalenko; Andrey Somov (IEEE Trans. Instrum. Meas., 2023)

Deep learning framework for neurological diseases diagnosis through near-infrared eye video and time series imaging algorithms. - Mohammed Hammoud; Ekaterina Kovalenko; Andrey Somov; Ekaterina Bril; Anna Baldycheva (Internet Things, 2023)