Computational Intelligence Induced Risk in Modern Healthcare

Abstract

The proliferation of IT has turned the healthcare industry up to a different level of automation, and this big leap in healthcare has also invited new challenges. Whether it is a small sensor or a complete room-based operating system, IoT plays a major role in saving lives while involving the new methodologies of medicines. From the remote collection of patient data, storage of electronic health records, facilitating drug delivery, demonstration of research-based drug trials, and synthesis or implementation of pathological results while providing functionality to patients and doctors, AI with IoT is transforming each and every component in this field. While providing great hand-holding capacity, IoT with AI also poses some major challenges and risks for both patients and doctors, such as handling sensitive data, patient consent and implementation of EULA, compliance of security standards in preserving the integrity of data either at transit or at storage, handling the socio-economics-based digital divide in remote areas, discrepancies in multiple vendors’ agreements, and its hierarchical implementation to achieve a common goal. This study catalogs all the major studies that have been conducted focusing on AI-based risks in IoT devices used in the field of medicine and healthcare. Challenges and future research directions have also been discussed, which can be helpful for creating better safeguards for minimizing the risk in automation-based devices where AI and IoT are at an intersection.

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