Smart Health Diagnosis, Prediction, and Preventive First Aid Using AI/ML

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare by enabling accurate diagnosis, early disease prediction, and real-time preventive interventions.This survey provides a comprehensive review of AI/ML-driven smart healthcare systems, focusing on algorithmic frameworks, data modalities, performance benchmarks, and deployment strategies.We analyze key architectures-including convolutional neural networks (CNNs), recurrent models, hybrid systems, and federated learning-applied to diagnostic imaging, clinical signal processing, and automated first aid.Recent advances in generative AI, edge computing, and multimodal fusion are examined to address challenges in data scarcity, latency, and interoperability.The study concludes with critical challenges-privacy, bias, explainability, and regulationand outlines future directions toward scalable, equitable, and trustworthy healthcare AI