The Chrono-Fourier AI Dataset: A Chronobiological Immune Time-Series Resource for Spectral Modeling of NLR/PLR/SII During Immune Checkpoint Therapy

The Chrono-Fourier AI Dataset is the first open-access chronobiological immune time-series dataset derived from real-world clinical data of patients treated with immune checkpoint inhibitors. It contains raw anonymized longitudinal laboratory measurements—including neutrophils, lymphocytes, platelets, and derived immune indices such as NLR, PLR, and SII—collected across sequential treatment cycles under PD-1, PD-L1, and CTLA-4 blockade. This dataset enables investigation of circadian timing effects, temporal immune dynamics, and immune coherence patterns in relation to therapy administration time (morning vs afternoon), clinical response, toxicity, and survival outcomes. It is specifically structured for Fourier-based spectral modeling and AI-driven time-series analysis, supporting machine learning exploration of rhythm-dependent immunologic behavior. The dataset is provided in CSV format and adheres to FAIR data principles for reproducibility, transparency, and real-world evidence development. It is compatible with Python, R, MATLAB, and modern deep learning frameworks, and is intended to support translational oncology research and future prospective chronotherapy trial design.