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)

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)

Employing Feature Selection Algorithms to Determine the Immune State of Mice with Rheumatoid Arthritis. - Brendon K. Colbert; Joslyn L. Mangal; Aleksandr Talitckii; Abhinav P. Acharya; Matthew M. Peet (CoRR, 2022)

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)

Integral Quadratic Constraints with Infinite-Dimensional Channels. - Aleksandr Talitckii; Matthew M. Peet; Peter Seiler 001 (ACC, 2023)

Efficient Convex Algorithms for Universal Kernel Learning. - Aleksandr Talitckii; Brendon K. Colbert; Matthew M. Peet (J. Mach. Learn. Res., 2024)

Employing Feature Selection Algorithms to Determine the Immune State of a Mouse Model of Rheumatoid Arthritis. - Aleksandr Talitckii; Joslyn L. Mangal; Brendon K. Colbert; Abhinav P. Acharya; Matthew M. Peet (IEEE J. Biomed. Health Informatics, 2024)