Integrating AI into Healthcare for Better Diagnosis and Quality
Using deep learning models (CNN, ViT) for automated EEG signal analysis, including artifact repair, anomaly detection, and disease classification. Supports multiple EEG formats (EDF, VHDR, FIF) with batch processing capabilities for clinical data.
Integrating large language models (LLM) to automatically generate structured medical reports based on EEG analysis results, reducing physician documentation burden and improving report consistency.
Integrating Gemini, Ollama, and other LLMs into healthcare information systems, providing intelligent Q&A, medical record summarization, medication recommendations, and other AI-assisted features.
Continuously investing in AI healthcare R&D, expanding to more clinical scenarios including medical image AI interpretation, smart nursing monitoring, and disease risk prediction.
CNN, ViT, Contrastive Learning, PyTorch
MNE-Python, EDF/VHDR/FIF format processing
Gemini API, Ollama, Report Generation
Model training, deployment, API service integration