Back to Search Start Over

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases.

Authors :
Marletta S
L'Imperio V
Eccher A
Antonini P
Santonicco N
Girolami I
Dei Tos AP
Sbaraglia M
Pagni F
Brunelli M
Marino A
Scarpa A
Munari E
Fusco N
Pantanowitz L
Source :
Pathology, research and practice [Pathol Res Pract] 2023 Mar; Vol. 243, pp. 154362. Date of Electronic Publication: 2023 Feb 06.
Publication Year :
2023

Abstract

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff. Thus, artificial intelligence (AI) has been exploited for identification of microorganisms. A systematic search was carried out using electronic databases looking for studies dealing with the application of AI to pathology microbiology specimens. Of 4596 retrieved articles, 110 were included. The main applications of AI regarded malaria (54 studies), bacteria (28), nematodes (14), and other protozoa (11). Most publications examined cytological material (95, 86%), mainly analyzing images acquired through microscope cameras (65, 59%) or coupled with smartphones (16, 15%). Various deep-learning strategies were used for the analysis of digital images, achieving highly satisfactory results. The published evidence suggests that AI can be reliably utilized for assisting pathologists in the detection of microorganisms. Further technologic improvement and availability of datasets for training AI-based algorithms would help expand this field and widen its adoption, especially for developing countries.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 Elsevier GmbH. All rights reserved.)

Details

Language :
English
ISSN :
1618-0631
Volume :
243
Database :
MEDLINE
Journal :
Pathology, research and practice
Publication Type :
Academic Journal
Accession number :
36758417
Full Text :
https://doi.org/10.1016/j.prp.2023.154362