Artificial intelligence innovation in healthcare
Literature review, exploratory analysis, and future research
Datos Bibliográficos
| ID | 11637610 |
|---|---|
| Autores | Ahmed Zahlan (0009-0008-8791-3238, Université Mohammed VI Polytechnique, autor de correspondencia), Ravi Prakash Ranjan (0009-0005-5531-9259, Université Mohammed VI Polytechnique), David Hayes (0000-0003-0484-4182, Université Mohammed VI Polytechnique) |
| Año | 2023 |
| Volumen | 74 |
| Páginas | 102321-102321 |
| Fecha de publicación | 2023-07-05 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Technology in Society (JOURNAL) |
| Identificadores de la revista | ISSN: 0160-791X • E-ISSN: 1879-3274 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techsoc.2023.102321 |
| OpenAlex | W4383216696 |
| Idioma | EN |
| Citas recibidas | 12 |
| Referencias citadas | 85 |
Artificial intelligence (AI) innovation in healthcare has emerged as an increasingly significant area of research. AI, digital data collection, and computer infrastructure advancements have empowered humans to address complex healthcare challenges. This study conducts a systematic literature review (SLR) of peer-reviewed journal articles at the intersection of AI, innovation, and healthcare to offer research directions for scholars and leaders in healthcare management. To achieve this, the systematic review identified and analyzed 378 published studies on AI innovation in healthcare. Evaluating these publications based on inclusion and exclusion criteria yielded 75 studies ultimately selected for comprehensive analysis. This research adds to the scope of previous investigations by aiming to 1) emphasize the most crucial AI-based healthcare applications, 2) explore challenges associated with AI integration in healthcare, and 3) examine student adoption and incorporation of AI into existing healthcare curricula. We also conducted an exploratory study of over 2700 AI-enabled healthcare startups worldwide to supplement our literature review. The SLR reveals several gaps within the research scope and proposes corresponding future research directions. These future research directions will assist researchers and enable healthcare professionals to develop legislation that accelerates the adoption of AI solutions in healthcare, ultimately enhancing public access to efficient and effective healthcare services
Business · Exploratory research · Health care · Knowledge management · MEDLINE · Political science · Scope (computer science · Sociology · Systematic review · Artificial Intelligence in Healthcare and Education · Biomedical and Engineering Education · Computer Science · Telemedicine and Telehealth Implementation
A Methodology for Investigating Technological Changes Driven by Social Events
Designing age-inclusive AI tutors
The longitudinal relationships between Internet adaptability and usage behavior on AI-driven healthcare platforms
Algorithmic emergence? Epistemic in/justice in AI-directed transformations of healthcare
Domesticating AI in medical diagnosis
The knowledge and innovation challenges of ChatGPT
Understanding digital therapeutics in disease self-management
Analyzing AI adoption in European SMEs
The influence of artificial intelligence techniques on disruption management
Digital transformation in healthcare operations
Healthcare organizations in entrepreneurial ecosystems
We're implementing AI now, so why not ask us what to do? - How AI providers perceive and navigate the spread of diagnostic AI in complex healthcare systems
Artificial intelligence in healthcare
Dermatologist-level classification of skin cancer with deep neural networks
Artificial intelligence in healthcare
Health Care Spending in the United States and Other High-Income Countries
Comparison of PubMed, Scopus, Web of Science, and Google Scholar
Machine learning in medicine
Medical students' attitude towards artificial intelligence
The potential for artificial intelligence in healthcare
Trust in Automation
User Acceptance of Information Technology
Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Artificial intelligence in healthcare
Will artificial intelligence solve the human resource crisis in healthcare
Artificial intelligence in health care
A progressive three-phase innovation to medical education in the United States
Chatbots for future docs
Do patients trust computers
Telehealth and Covid-19
What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics
Is AI intelligent? An assessment of artificial intelligence, 70 years after Turing
Artificial intelligence, systemic risks, and sustainability
Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities
Understanding the acceptance of emotional artificial intelligence in Japanese healthcare system
Applied Artificial Intelligence and user satisfaction
| Obras citantes distintas | 12 |
|---|---|
| Citas por año | 4 |
| Intervalo de citas | 2023 - 2026 (4) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 11 |