Cargando…
Identifying Disease of Interest With Deep Learning Using Diagnosis Code
BACKGROUND: Autoencoder (AE) is one of the deep learning techniques that uses an artificial neural network to reconstruct its input data in the output layer. We constructed a novel supervised AE model and tested its performance in the prediction of a co-existence of the disease of interest only usin...
Autores principales: | Cho, Yoon-Sik, Kim, Eunsun, Stafford, Patrick L., Oh, Min-hwan, Kwon, Younghoon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Academy of Medical Sciences
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027541/ https://www.ncbi.nlm.nih.gov/pubmed/36942391 http://dx.doi.org/10.3346/jkms.2023.38.e77 |
Ejemplares similares
-
Deep Learning for the Pathologic Diagnosis of Hepatocellular Carcinoma, Cholangiocarcinoma, and Metastatic Colorectal Cancer
por: Jang, Hyun-Jong, et al.
Publicado: (2023) -
Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers
por: Lim, Jayeon, et al.
Publicado: (2019) -
Identifying the Medical Lethality of Suicide Attempts Using Network Analysis and Deep Learning: Nationwide Study
por: Kim, Bora, et al.
Publicado: (2020) -
Combined Deep Learning Techniques for Mandibular Fracture Diagnosis Assistance
por: Son, Dong-Min, et al.
Publicado: (2022) -
Applying Deep Learning Model to Predict Diagnosis Code of Medical Records
por: Masud, Jakir Hossain Bhuiyan, et al.
Publicado: (2023)