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Магистратура 2023/2024

Большие данные и машинное обучение в медицине

Статус: Курс по выбору (Науки о данных (Data Science))
Направление: 01.04.02. Прикладная математика и информатика
Когда читается: 2-й курс, 1, 2 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Прогр. обучения: Науки о данных
Язык: английский
Кредиты: 6
Контактные часы: 50

Course Syllabus

Abstract

Medical Informatics (MI) is a new, exponentially-growing field, where information sciences meet modern clinical applications. The main goal of this class in to introduce HSE students to the broad spectrum of MI problems and applications, and to provide the students with the skills necessary for conduction professional MI work.
Learning Objectives

Learning Objectives

  • To develop fundamental knowledge of concepts underlying medical informatics projects.
  • To develop practical skills needed in modern digital medicine.
  • To explain how math and information sciences can contribute to building better healthcare.
  • To give a hands-on experience with real-world medical data analysis.
  • To develop applied experience with medical software, programming, applications and processes.
Expected Learning Outcomes

Expected Learning Outcomes

  • Students are fluent in clinical data acquisition, processing and management, in the areas outlined in the schedule.
  • Students know the basic concepts of MI.
Course Contents

Course Contents

  • Introduction: What is MI, and what it is not
  • Standards: Overview and HL7
  • Standards: DICOM
  • Making sense of standards
  • Computed tomography; Image enhancement
  • Computer-Aided Diagnostics (CAD)
  • Networking and teleradiology
  • Security
  • Scheduling and queuing
  • Simulation/Modeling in Medicine
  • Clinical software development; Medical startups
  • Medical startups
  • Unusual applications
Assessment Elements

Assessment Elements

  • non-blocking Class homework/projects, assigned after each lecture
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2023/2024 2nd module
    0.8 * Class homework/projects, assigned after each lecture + 0.2 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Pianykh, O. S. Digital imaging and communications in medicine (DICOM): a practical introduction and survival guide. – Springer Science & Business Media, 2009. – 417 pp.

Recommended Additional Bibliography

  • Pianykh O. S. Digital Image Quality in Medicine. – Springer International Publishing, 2014. – 140 pp.

Authors

  • PYANYKH OLEG STANISLAVOVICH
  • Антропова Лариса Ивановна