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title: README
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Hi 👋, we are the PRAISE Research Group
Predictive Analytics for Understanding Big Multimedia Data @ University of Naples Federico II
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## 🧠 About Us
The **PRAISE (PRedictive AnalytIcs for underStanding big multimEdia data)** research group is part of the **PICUS Lab** at the **Department of Electrical Engineering and Information Technologies (DIETI)**, University of Naples Federico II, Italy.
We are a team of researchers with a strong background in **AI**, **multimodal data understanding**, and **predictive analytics** across multiple domains including **eHealth**, **Social Network Analysis**, and **Multimedia Data Analysis**.
Our goal is to develop intelligent systems that can **understand**, **predict**, and **interact** with complex multimedia information—especially focusing on language, vision, and their integration.
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## 🔬 Research Topics
- **Multimodal AI for Healthcare**
- Multilingual and multimodal language models
- Diagnostic and therapeutic AI assistance
- Automatic EHR generation from speech and unstructured text (Italian)
- Medical image understanding (CT, MRI, X-ray, etc.)
- **Social Network Modeling & Simulation**
- Generative Agent-Based Frameworks
- LLM-driven simulation of social phenomena: stance change, information diffusion
- Tools for crowd fact-checking, fake news and harmful content detection
- **Lie Detection from Multimedia Streams**
- AI for behavioral analysis and deception detection
- Collaborative project with US-based Courtscribes Company
- **Big Scholarly Data Analytics**
- Automated knowledge extraction and semantic enrichment
- Development of analytics platforms for scientific literature
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## 🤖 Models
We are currently developing **fine-tuned multimodal language models** for the **Italian medical domain**, in collaboration with national (e.g., Accenture, Almaviva) and international partners (e.g., King’s College London).
Our models integrate **textual** and **visual** medical data to support clinical tasks in real-world applications.
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## 📄 View our papers
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## 📫 Contact Us
- 🌐 **GitHub Page:** [PRAISELab@PICUSLab](https://github.com/PRAISELab-PicusLab)
Connect with us:
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## ⭐ Members
