Multi-modality artificial intelligence in digital pathology.
Brief Bioinform
; 23(6)2022 11 19.
Article
en En
| MEDLINE
| ID: mdl-36124675
ABSTRACT
In common medical procedures, the time-consuming and expensive nature of obtaining test results plagues doctors and patients. Digital pathology research allows using computational technologies to manage data, presenting an opportunity to improve the efficiency of diagnosis and treatment. Artificial intelligence (AI) has a great advantage in the data analytics phase. Extensive research has shown that AI algorithms can produce more up-to-date and standardized conclusions for whole slide images. In conjunction with the development of high-throughput sequencing technologies, algorithms can integrate and analyze data from multiple modalities to explore the correspondence between morphological features and gene expression. This review investigates using the most popular image data, hematoxylin-eosin stained tissue slide images, to find a strategic solution for the imbalance of healthcare resources. The article focuses on the role that the development of deep learning technology has in assisting doctors' work and discusses the opportunities and challenges of AI.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Inteligencia Artificial
Límite:
Humans
Idioma:
En
Año:
2022
Tipo del documento:
Article