Anomaly Detection and Deep Vein Thrombosis Prediction using Machine Learning and Secure Data Storage using Blockchain

An AI-powered companion system is proposed to enhance astronaut health monitoring and mitigate risks, particularly Deep Vein Thrombosis (DVT). By analyzing health data collected via IoT wearables, the system establishes personalized baselines and employs machine learning algorithms to detect anomalies indicative of potential health issues. Predictive models, trained on historical astronaut health data, identify patterns associated with DVT risk, enabling early intervention. Securely transmitted health data and risk assessments support remote medical consultations and proactive care. This system has the potential to significantly reduce DVT incidence, improve astronaut well-being, and enhance mission success by enabling timely medical interventions and optimizing resource allocation.