This educational repository focuses on working with three types of medical data: tabular data, ECG and EEG signals. It provides implementations of machine learning and deep learning models for processing and analyzing these medical data, with practical projects based on recent research articles.

API de suporte à decisão clínica para síntese de laudos de ECG utilizando LLM e HL7 FHIR

FPGA implementation of Tiny Transformer with dynamic adaptive attention for ECG arrhythmia classification. Introduced is features learnable head gating mechanism that adaptively selecta attention heads. Targeted FPGA board is Xilinx Kria KV260 and development was done in Vitis HLS and deployment through PYNQ Overlays.