Hello, ML enthusiasts! 🎉 We’ve reached the final session of the ML Paper Reading Club, and we’re ending on a high note with an incredible paper that combines machine learning and medical imaging to tackle a critical healthcare challenge. 🧠💻

This session will focus on the use of unsupervised machine learning to identify subtypes of multiple sclerosis (MS) using MRI data. It’s a groundbreaking study that showcases the power of ML in advancing medical research. 🏥🔬

What’s in store for this session?

📄 Eshaghi, A., Young, A.L., Wijeratne, P.A., Prados, F., Arnold, D.L., Narayanan, S., Guttmann, C.R.G., Barkhof, F., Alexander, D.C., Thompson, A.J., Chard, D. and Ciccarelli, O. (2021) ‘Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data’, Nature communications, 12(1), pp. 2078–2078. 

This paper, published in Nature Communications, demonstrates how unsupervised ML can be used to classify MS subtypes, offering new insights into personalized treatment strategies. 🎯

🔗 Read the paper here

Why should you join?

✅ Learn & Grow: Deepen your understanding of ML concepts and methodologies.
✅ Community: Share insights, ask questions, and discuss ideas with peers.
✅ Recognition: Get a certificate and a prize if you attend at least 3 out of 4 sessions! 🏆
✅ Critical Thinking: Write a critical post summarizing and sharing your thoughts on one of the papers.

How does it work?

1️⃣ Read the paper: Come prepared to discuss the fourth paper on 25th February.
2️⃣ Engage: Share your thoughts, ask questions, and learn from others.
3️⃣ Write: After the session, write a critical post about the paper and share your insights.
4️⃣ Repeat: Join us for the next sessions throughout February!