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Journal
/
Bioengineering
/
AI Program for Trypanosomiasis Detection and Classification
/
AI-Driven Trypanosome Species Detection from Microscopic Images (Video) | JoVE
JoVE Journal
Bioengineering
Author Produced
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JoVE Journal
Bioengineering
Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model
AI-Driven Trypanosome Species Detection from Microscopic Images (Video) | JoVE
AI Program for Trypanosomiasis Detection and Classification
DOI:
10.3791/65557-v
•
01:29 min
•
October 27, 2023
•
Veerayuth Kittichai
,
Morakot Kaewthamasorn
,
Suchansa Thanee
,
Thanyathep Sasisaowapak
,
Kaung Myat Naing
,
Rangsan Jomtarak
,
Teerawat Tongloy
,
Santhad Chuwongin
,
Siridech Boonsang
1
Faculty of Medicine
,
King Mongkut’s Institute of Technology Ladkrabang
,
2
Veterinary Parasitology Research Unit, Faculty of Veterinary Science
,
Chulalongkorn University
,
3
College of Advanced Manufacturing Innovation
,
King Mongkut’s Institute of Technology Ladkrabang
,
4
Faculty of Science and Technology
,
Suan Dusit University
,
5
Department of Electrical Engineering, School of Engineering
,
King Mongkut’s Institute of Technology Ladkrabang
Tags
Trypanosome
Trypanosoma Cruzi
T. Brucei
T. Evansi
Deep Learning
Object Detection
Object Classification
Microscopic Images
AI Model
Hybrid Deep Learning
CiRA CORE
Trypanosomiasis
Automated Screening
Microscopic Examination
Pattern Recognition
Attention Map
Accuracy
Recall
Specificity
Precision
F1 Score
ROC
PR Curves
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