Biology basics, python basics
Provide the knowledge required
- prepare a statistically correct experiment based on the objectives of the study
- to describe and statistically analyze the data collected
- to correctly interpret and communicate results.
Target skills
At the end of the course, students should be able to:
- Methodically approach an experimental protocol.
- Master simple data mining tools.
- Master the choice of a simple statistical model that best represents the data.
- Master the choice of a decision-making tool (statistical test) appropriate to the experimental context.
As a result, they must be able to acquire a critical eye enabling them to analyze
the results of a survey or experiment.
This course covers the various modern medical imaging modalities frequently encountered in the diagnosis and treatment of cancer.
cancer treatment.
The course focuses on 3 areas: theory, programming and communication. It covers the theoretical foundations of probability, in the context of sampling devices and random variables. Normal law, from which interval estimation methods and hypothesis testing are studied. Linear models explored with quantitative, qualitative and combinations of these variables and their interactions.
Least squares and maximum likelihood methods. Generalized linear models for frequency and proportion analysis.
Programming with Python.
Medical imaging modalities
2D and 3D tomographic reconstruction
Multimodal processing and analysis
Volume visualization
Python and medical imaging
Proctored homework.
