This work focuses on automated hemorrhage detection on head CT using a deep learning pipeline that produces slice-level predictions for intracranial hemorrhage classes and an overall abnormality estimate. The viewer presents each slice as a combined panel with the CT image, a saliency overlay showing which regions most influenced the model, and class-probability bars to summarize predicted findings.