Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone
Abstract High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist review of histologic slides provides no p...
Guardado en:
Autores principales: | Anna Ray Laury, Sami Blom, Tuomas Ropponen, Anni Virtanen, Olli Mikael Carpén |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/dec4332aac824453a0d7dbb9e180088a |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automatic Grading Tool for Jupyter Notebooks in Artificial Intelligence Courses
por: Cristian D. González-Carrillo, et al.
Publicado: (2021) -
Predicting Post-Therapeutic Visual Acuity and OCT Images in Patients With Central Serous Chorioretinopathy by Artificial Intelligence
por: Fabao Xu, et al.
Publicado: (2021) -
Artificial intelligence can assist with diagnosing retinal vein occlusion
por: Qiong Chen, et al.
Publicado: (2021) -
Can Autism Be Diagnosed with Artificial Intelligence? A Narrative Review
por: Ahmad Chaddad, et al.
Publicado: (2021) -
Molecular analysis of high-grade serous ovarian carcinoma with and without associated serous tubal intra-epithelial carcinoma
por: Jennifer Ducie, et al.
Publicado: (2017)