AI Driven Smart Healthcare: A Comprehensive Survey of Data Collection, IoT Enabled Sensing, 5G/6G Communications and Deep Learning for Early Diagnosis
Year: 2025
Type: article
Abstract: The healthcare sector continues to face significant challenges in disease prediction, with late diagnoses exposing limitations in existing systems.Artificial Intelligence (AI) has emerged as a transformative force, reshaping patient data management, diagnostic processes, and treatment strategies.AI-enabled healthcare systems optimize diagnostic processes leveraging machine learning (ML) and deep learning (DL) techniques to optimize diagnostics and decision-making.Data collectionoften driven by wireless sensors and IoT-enabled healthcare devices-serves as a critical foundation for training these models.In this paper, we first present an overview of AI applications in healthcare, focusing on data acquisition, IoT-based sensing, and the role of 5G and 6G communications in enabling realtime healthcare services.We then explore system recommendation frameworks and CNN-based image captioning models for medical imaging analysis.The role of deep neural networks (DNNs) in powering smart healthcare systems is discussed in detail, alongside the potential of Software Defined Radio (SDR) technology for monitoring respiratory diseases.We also examine the use of Intelligent Reflecting Surfaces (IRS) to enhance wireless communication reliability in medical environments.Finally, we highlight key challenges and ethical considerations in the design and deployment of AI-driven smart healthcare systems.
Authors: Qurat Ul Ain, Rameez Asif
Institution: Xidian University
Language: English
Topic: Internet of Things and AI
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414497060
FWCI:
Cites:
Cited by:
Related to: