Cargando…
Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study
BACKGROUND: This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans. METHODS: Until May 2023, systematic searches were conducted in ISI Web of Sci...
Autores principales: | Maghami, Masoud, Sattari, Shahab Aldin, Tahmasbi, Marziyeh, Panahi, Pegah, Mozafari, Javad, Shirbandi, Kiarash |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694901/ http://dx.doi.org/10.1186/s12938-023-01172-1 |
Ejemplares similares
-
The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis
por: Moezzi, Meisam, et al.
Publicado: (2021) -
Machine learning algorithms for diagnosis of hip bone osteoporosis: a systematic review and meta-analysis study
por: Rahim, Fakher, et al.
Publicado: (2023) -
C(2)HEST score for atrial fibrillation risk prediction models: a Diagnostic Accuracy Tests meta-analysis
por: Haybar, Habib, et al.
Publicado: (2021) -
Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
por: Chegeni, Nahid, et al.
Publicado: (2019) -
Environmental concern regarding the effect of humidity and temperature on 2019-nCoV survival: fact or fiction
por: Harmooshi, Narges Nazari, et al.
Publicado: (2020)