Student thesis.
“Driving progress, one thesis at a time.”
Are you thinking about your Master or PhD thesis? Are you unsure where to start?
At Medtiles we have extensive experience in supervising and mentoring academic thesis at all levels.
Get in contact and explore your next academic adventure with us!
Teaching and Courses.
“Education is the compass that guides us to a brighter tomorrow.”
As part of our mission in the healthcare sector, teaching Artificial Intelligence is one of the pillars that defines us.
“Data Science for Healthcare“ is course developed entirely by Medtiles team, and seeks to prepare all healthcare professionals for the technological future of AI. From python basics to predictive models, learn how to handle data and machine learning for your own research.
Get in touch if you want to learn more about the course. If you are willing to attend or host the course for your team, reserve your seat through the contact form with the subject “DS for Healthcare“.
Research
“It all begins with an idea.”
Maybe you feel like you have the right idea but it’s difficult to start? Maybe you have not a team to begin with? Or just want to discuss your prototype with us?
Either if you are individual researcher or a company with the need for a disruptive solution in health, we want to hear from you.
Get in touch and let’s know each other.
Data Science for Healthcare
From Python basics to machine learning, take AI with you for the future….
Syllabus
Module 1.
Artificial Intelligence Introduction & Python Basics
- Introduction to Artificial Intelligence & Data Science.
- Python programming basics.
- Major examples of AI in Healthcare.
Module 2.
Data Wrangling
- Medical data visualization and pre-processing.
- Main medical databases and data access points.
- Medical exploratory data analysis.
Module 3.
Unsupervised Learning
- Finding and optimizing hidden patterns in patient and healthcare data;
- Pattern profiling and actionable insights for healthcare data records.
Module 4.
Supervised Learning
- How to correctly train and validate a machine learning model for stroke prediction;
- Regression vs Classification tasks: patient risk score vs probability of having a disease.
- Explainability of predictions: Know why your model predicted a positive patient stroke.
Module 5.
Data Science scenarios
- Discussion about real world data and machine learning challenges in medical and industrial projects.
Artificial Intelligence for Healthcare
From Data Science to ChatGPT, understand how Generative Artificial Intelligence is transformation Healthcare
Syllabus
Module 1.
Data Science & Machine learning Introduction
- What is Artificial Intelligence and how it’s organised
- Overview of Supervised, Unsupervised and Reinforcement Learning.
- How do I know what a good AI system is.
Module 2.
Fundamentals of Generative Artificial Intelligence
- Introduction to Generative AI and difference from Traditional AI.
- What is an LLM and the AI trinomial: Architectures, Infrastructure and Energy.
- Generative AI for Healthcare: LLMs and use cases
- Introduction to Agentic IA.
Module 3.
Practical Application of GenAI in Healthcare
- Healthcare use cases: from chating with documents to systemic reviews;
- Tools: NotebookLM, Perplexity, Google Gemini, Google Gems, OpenAI Agent Builder and n8n.
Module 4.
Regulation, Ethics and Risks in AI for Healthcare
- Main risks of AI use in Healthcare and brief overview of AI Act.
- Bias, Transparency and Explainability.
- Best practises
Interested in Learning about AI? Get in contact.
Either if you want to attend one of our courses or organize one yourself together with Medtiles, don’t be shy…talk to us!
