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

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 ski...

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Published in:Pathology, research and practice research and practice, 2023-03, Vol.243, p.154362-154362, Article 154362
Main Authors: Marletta, Stefano, L’Imperio, Vincenzo, Eccher, Albino, Antonini, Pietro, Santonicco, Nicola, Girolami, Ilaria, Dei Tos, Angelo Paolo, Sbaraglia, Marta, Pagni, Fabio, Brunelli, Matteo, Marino, Andrea, Scarpa, Aldo, Munari, Enrico, Fusco, Nicola, Pantanowitz, Liron
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Cytopathology
Databases, Factual
Deep learning
Humans
Infectious diseases
Malaria
Microorganisms
Microscopy
Pathologists
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Summary: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.
ISSN:0344-0338
1618-0631
DOI:10.1016/j.prp.2023.154362