An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research
| Autor: | Leo Anthony Celi, Beatrice Tiangco, Sanjay Budhdeo, Maria del Pilar Arias Lopez, Hutan Ashrafian, Piyawat Lertvittayakumjorn, Jack Gallifant, Stephen Whebell, Joe Zhang, Heather Mattie, James T. Teo, Judy Wawira Gichoya |
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| Rok vydání: | 2022 |
| Předmět: |
Computer science
business.industry Dashboard (business) MEDLINE Equity (finance) Medicine (miscellaneous) Health Informatics Track (rail transport) Pipeline (software) Maturity (finance) Article Health Information Management Artificial Intelligence Decision Sciences (miscellaneous) Artificial intelligence business |
| Zdroj: | Lancet Digit Health |
| ISSN: | 2589-7500 |
| DOI: | 10.1016/s2589-7500(22)00032-2 |
| Popis: | The global clinical artificial intelligence (AI) research landscape is constantly evolving, with heterogeneity across specialties, disease areas, geographical representation, and development maturity. Continual assessment of this landscape is important for monitoring progress. Taking advantage of developments in natural language processing (NLP), we produce an end-to-end NLP pipeline to automate classification and characterization of all original clinical AI research on MEDLINE, outputting real-time results to a public, interactive dashboard (https://aiforhealth.app/). |
| Databáze: | OpenAIRE |
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