AI-powered microscopy image analysis for parasitology: integrating human expertise.
Trends Parasitol
; 40(7): 633-646, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-38824067
ABSTRACT
Microscopy image analysis plays a pivotal role in parasitology research. Deep learning (DL), a subset of artificial intelligence (AI), has garnered significant attention. However, traditional DL-based methods for general purposes are data-driven, often lacking explainability due to their black-box nature and sparse instructional resources. To address these challenges, this article presents a comprehensive review of recent advancements in knowledge-integrated DL models tailored for microscopy image analysis in parasitology. The massive amounts of human expert knowledge from parasitologists can enhance the accuracy and explainability of AI-driven decisions. It is expected that the adoption of knowledge-integrated DL models will open up a wide range of applications in the field of parasitology.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Parasitology
/
Image Processing, Computer-Assisted
/
Artificial Intelligence
/
Microscopy
Limits:
Humans
Language:
En
Journal:
Trends Parasitol
/
Trends in parasitology
/
Trends parasitol
Journal subject:
PARASITOLOGIA
Year:
2024
Document type:
Article
Affiliation country:
Australia
Country of publication:
Reino Unido