About this Research Topic
The inexorable surge in both volume and complexity of the influx of data in healthcare have given rise to the application of machine learning (ML) and artificial intelligence (AI) within the field. It is expected that AI and ML will be used increasingly in the early diagnosis of diseases, clinical trials, robotic surgeries, patient engagement and adherence, and healthcare administration. As the scope and depth of these use cases grow, more effective deployment of ML and AI solutions shall become a necessity. Many believe that the next generation of breakthroughs in healthcare will be accomplished or at least seeded by the discoveries with AI and ML. With this imminent outlook for the future of healthcare, many enterprises feel the urge to start planning for a comprehensive ML and AI strategy.
Regarding the rising importance of ML and AI in the healthcare sector, we invite submissions that shed more light on how these technologies can best be incorporated into various parts of the industry. We are interested in topics such as novel and trending applications of ML and AI in healthcare, pre-adoption assessments and models of enterprise readiness, post-adoption consequences, potential implementation and ethical issues, engagement and integration aspects, patient and staff training, and clinical diagnosis and treatment support.
While we value manuscripts that derive their conclusions based on real data sets, this Research Topic also welcomes conceptual papers as well as those that synthesize current trends in the industry to build broader and more encompassing pictures for the use and application of ML and AI in healthcare:
· Models to assess the readiness of a healthcare firm to adopt ML and AI.
· The strategic aspects (pros and cons) of adopting ML and AI in healthcare.
· Novel and trending applications of ML and AI in healthcare such as early disease diagnostics, imaging diagnostics, predictive prognostics, prescriptive survival analysis, natural language processing (NLP) of clinical transcripts and/or published medical literature, and Robotic Process Automation (RPA).
· The future of health, healthy-life and wellbeing supported by ML and AI.
· Ethical aspects of using ML and AI in healthcare.
· The future of employment in healthcare and how jobs will be affected by ML and AI (e.g., what jobs may be lost and what new jobs will be created).
· Potentials for innovation, such as new business models and applications in healthcare that will be driven by ML and AI.
Keywords: Business, Healthcare, Machine Learning, Artificial Intelligence, Technology Adoption, Analytics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
