Cargando…
Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning
Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Vario...
Autores principales: | Hong, Gil-Sun, Jang, Miso, Kyung, Sunggu, Cho, Kyungjin, Jeong, Jiheon, Lee, Grace Yoojin, Shin, Keewon, Kim, Ki Duk, Ryu, Seung Min, Seo, Joon Beom, Lee, Sang Min, Kim, Namkug |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613849/ https://www.ncbi.nlm.nih.gov/pubmed/37724586 http://dx.doi.org/10.3348/kjr.2023.0393 |
Ejemplares similares
-
Developing a Cancer Digital Twin: Supervised Metastases Detection From Consecutive Structured Radiology Reports
por: Batch, Karen E., et al.
Publicado: (2022) -
Building One-Shot Semi-Supervised (BOSS) Learning Up to Fully Supervised Performance
por: Smith, Leslie N., et al.
Publicado: (2022) -
Self-supervised recurrent depth estimation with attention mechanisms
por: Makarov, Ilya, et al.
Publicado: (2022) -
Supervised machine learning models for depression sentiment analysis
por: Obagbuwa, Ibidun Christiana, et al.
Publicado: (2023) -
Vector representation based on a supervised codebook for Nepali documents classification
por: Sitaula, Chiranjibi, et al.
Publicado: (2021)