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Summer SchoolMedicine and Machine Learning

Medicine and Machine Learning

Summer School - On campus
July 14 - July 25, 2025

The course also can be arranged as the tailor-made programe for a group of minimum 10 students upon request (the dates and terms can be discuss individually)

Want to go deep into analysing and processing medical data using machine learning techniques? Join this summer school!

Medicine-and-Machine-Learning
Medicine-and-Machine-Learning
  • Brief description

    This course is for students with the knowledge and skills to analyse medical data using Machine Learning. By the end of the course, students will be able to apply ML techniques to practical problems in medical data analysis, with examples on ECG and Parkinson's disease data.

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Duration: 2 weeks

ECTS credits: 4.0

Participation fee: 50 000 RUB

Deadline for registration: May 18, 2025

  • Cultural program

    We offer our students excursions to the most famous palaces, monuments, museums of St. Petersburg, as well as other cultural activities.

  • Entrance requirements
    • • The course is open for Bachelor, Master and PhD students with the background in Information Technology and Computer Science, Mathematical Science or equivalent skills and knowledge;
    • • Good command of English. All classes and extracurricular activities are carried out in English. Knowledge of the Russian language is not required;
    • • Applicants are expected to have at least 1 year of University level studies.
  • Course description

    The following topics will be covered:

    • • Introduction to Medical Data and Machine Learning in Healthcare;
    • • Overview of Neural Networks and Convolutional Neural Networks;
    • • Theory and Applications of EMG Data in Medical Analysis;
    • • Introduction to Heart Anatomy, Heart Diseases, and ECG Data;
    • • Practical Applications of ECG Data Analysis with Python;
    • • Brain Anatomy, Neurological Diseases, and EEG Data Analysis;
    • • EEG Data Processing and Machine Learning Applications;
    • • Understanding Parkinson’s Disease and Its Data Challenges;
    • • Machine Learning Techniques for Analysing Parkinson’s Disease Data;
    • • Practical Applications of Convolutional Neural Networks in Medical Data;
    • • Workflow for Medical Data Analysis with Python;
    • • Ethical Considerations in Medical Data and Machine LearningEthical Considerations in Medical Data and Machine Learning.

The detailed course description for ECTS credits transfer at your home university:

Medicine and Machine Learning Descriptor.pdf

REGISTER ONLINE

Professors and lecturers:

  • Ogul Unal - PhD, Institute of Computer Science and Technology, SPbPU; M-com Search Engine Optimization specialist”.

Contacts:

Summer and Winter Schools Team