Applications of AI in healthcare

Applications of AI in healthcare

            In the beginning, technology was only used to automate the most mundane and repetitive jobs and to reduce the use of paper by digitizing health records while also facilitating the simple flow of information between health insurers, hospitals, and patients, among other things. Meanwhile, as these activities continue to be worked on, Artificial Intelligence has broadened its applications beyond those previously limited to boosting back-office efficiency to emerge as a critical facilitator for improving healthcare results. AI can significantly increase productivity, efficiency, workflow, accuracy, and speed, both for healthcare professionals and patients, by supplementing human performance in various ways.

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            Many digital health technologies, such as conversational agents, are being developed to solve existing health care concerns, such as a scarcity of health care workers, which reduces the accessibility and availability of medical services. Conversational agents utilize AI technology, notably deep learning (a statistical technique for training models using data to generate forecasts based on some variables), and natural language processing – the capacity to detect and understand verbal and written information), to communicate with people through voice, text, or any other inputs and outputs on smartphones, web-based, or audio-based systems. Users may converse with these robots in the same way they would with a human being because of the widespread usage of natural language processing (NLP). This gives the agent a chance to process the data and answer conversationally.         

According to Milne-Ives et al. (2020), the growing demand for medical services and the increasing capability of AI technologies have resulted in the emergence of conversational agents capable of assisting with a wide range of health-related practices, including behavior modification, treatment assistance, monitoring systems, teaching, triage, and screening assistance. In recent decades, conversational agents (a.k.a. chatbots) have grown into multimodal, multipurpose platforms capable of automating a varied variety of health-related operations that benefit the general population, patients, and clinicians (de Cock et al., 2020).  Automation of these processes might allow doctors to concentrate on more challenging jobs, increasing public access to health care services. A comprehensive review of these agents’ acceptability, usefulness, and efficacy in medical assistance is required to compile the evidence and identify opportunities for improvement and the possibility for sustainable uptake in future development. 

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