Adopting Artificial Intelligence in Healthcare: A Narrative Review

Introduction

During the last ten years, the development, adoption, and implementation of digital transformation have grown in many areas, including the field of healthcare. In their book entitled “Integrating Digital Health Strategies for Effective Administration”, Bouarar et al. (2023a) mentioned that “the switch towards digital healthcare is of a vital importance since it creates opportunities for doctors to gain a holistic view of their patients’ health and for patients to enjoy a swift and better healthcare services.” This transformation relies strongly on modern technological innovations such as augmented reality, 3D Printing, Internet of Things, robotics and big data, besides artificial intelligence (AI). In addition, the COVID-19 health crisis constituted a public health emergency in most countries of the world (Bouarar et al., 2023b; Cannavale et al., 2022; Mouloudj & Bouarar, 2023). As a result, health organizations adopted digital solutions (Bouarar et al., 2022; Bovsh et al., 2023; YahiaMarzouk, 2023), such as digital innovation (Bouabdellah, 2023), digital health apps (Mouloudj et al., 2023), and AI technology (Köse, 2023). According to Fan et al. (2020, p. 568), “applying the AI technology to the problem of medical diagnosis is expected, to assist physicians in their routine work to improve the diagnostic level and alleviate their work pressure significantly.” Hence, the proper adoption of AI technology in the healthcare sector provides a useful remedy for some of the challenges that health systems in various countries suffer from (Petersson et al., 2022). However, according to Na and Sheu (2022, p.1), mobile health (mHealth) technologies “may create additional barriers to health equity in the absence of equitable distributions of socioeconomic resources and access to mobile devices and the Internet.”

Adopting AI reaps many benefits, yet many organizations still struggle to adopt AI technology (Neumann et al., 2022). This is due to the presence of many organizational, financial, technological, and human obstacles that limit the adoption of AI in a smooth manner. Furthermore, the market for AI systems is growing due to their gains, nonetheless, without successful applications, these gains cannot be reaped (Merhi, 2022). Where there is a high rate of failure to adopt digital transformation and AI with significant financial losses (George & Howard, 2023). Nowadays, AI technologies are being used in various healthcare disciplines like radiology (Thrall et al., 2018), radiotherapy (Hindocha et al., 2023), ophthalmology (Kapoor et al., 2019; Shetty et al., 2021), surgery (Hashimoto et al., 2018; Zhou et al., 2020), oncology (D’Amore et al., 2021), gynecologic (Mysona et al, 2021; Shrestha et al., 2022), and cardiology (e.g. Dorado-Díaz et al., 2019; Itchhaporia, 2022; Johnson et al., 2019; Lopez-Jimenez et al., 2020; Nakamura & Sasano, 2022). Accordingly, the use of artificial intelligence in almost all medical specialties has expanded rapidly in recent years.