AI Program for Trypanosomiasis Detection and Classification

October 27th, 2023

AI-Driven Trypanosome Species Detection from Microscopic Images (Video) | JoVE

01:29 min

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Training Process CiRA CORE Platform and Object Detection Model Evaluation to Identify and Classify the Protozoan Trypanosome Species (Video) | JoVE

04:00 min

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Image Classification as Model Training and Model Evaluation to Identify and Classify the Protozoan Trypanosome Species (Video) | JoVE

01:37 min

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Hybrid (Detection and Classification) as Model Testing to Identify and Classify the Protozoan Trypanosome Species (Video) | JoVE

01:26 min

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Veerayuth Kittichai¹, Morakot Kaewthamasorn², Suchansa Thanee², Thanyathep Sasisaowapak³, Kaung Myat Naing³, Rangsan Jomtarak⁴, Teerawat Tongloy³, Santhad Chuwongin³, Siridech Boonsang⁵

¹Faculty of Medicine, King Mongkut’s Institute of Technology Ladkrabang, ²Veterinary Parasitology Research Unit, Faculty of Veterinary Science, Chulalongkorn University, ³College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang, ⁴Faculty of Science and Technology, Suan Dusit University, ⁵Department of Electrical Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang

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Verdensomspennende medisinske blodparasitter ble automatisk screenet ved hjelp av enkle trinn på en AI-plattform med lav kode. Den prospektive diagnosen av blodfilmer ble forbedret ved å bruke en objektdeteksjons- og klassifiseringsmetode i en hybrid dyplæringsmodell. Samarbeidet mellom aktiv overvåking og godt trente modeller bidrar til å identifisere hotspots av trypanosomoverføring.

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AI Program for Trypanosomiasis Detection and Classification

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