狂犬病対策に役立つ犬の顔認識アプリを開発(Facial recognition app for dogs developed to help in fight against rabies)

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2024-01-24 ワシントン州立大学(WSU)

◆新しいモバイルベースの犬の顔認識アプリが、アフリカやアジアなどの狂犬病ワクチン接種の努力を向上させる可能性があるとする研究が発表されました。ワシントン州立大学の研究者が開発したこのアプリは、タンザニアの地方で行われた狂犬病ワクチンクリニックでの効果をテストし、適切な画像と情報がデータベースから取り除かれた後、非常に正確であることが示されました。◆アプリを使用することで、運営者は接種済み犬の76.2%と未接種犬の98.9%を識別できました。狂犬病は年間約60,000人の死亡を引き起こし、アフリカとアジアでほぼ全てが犬による咬傷の結果です。この新技術は、ワクチン接種プログラムの成功において、正確かつ効率的にワクチン接種を受けた犬を特定する能力が重要であるとされる状況で、有望なツールとなる可能性があります。

<関連情報>

ワクチン接種実施済み犬を識別するための新しい顔認識技術のテスト Testing novel facial recognition technology to identify dogs during vaccination campaigns

Anna Maria Czupryna,Mike Estepho,Ahmed Lugelo,Machunde Bigambo,Maganga Sambo,Joel Changalucha,Kennedy Selestin Lushasi,Philip Rooyakkers,Katie Hampson & Felix Lankester
Scientific Reports  Published:12 December 2023
DOI:https://doi.org/10.1038/s41598-023-49522-2

狂犬病対策に役立つ犬の顔認識アプリを開発(Facial recognition app for dogs developed to help in fight against rabies)

Abstract

A lack of methods to identify individual animals can be a barrier to zoonoses control. We developed and field-tested facial recognition technology for a mobile phone application to identify dogs, which we used to assess vaccination coverage against rabies in rural Tanzania. Dogs were vaccinated, registered using the application, and microchipped. During subsequent household visits to validate vaccination, dogs were registered using the application and their vaccination status determined by operators using the application to classify dogs as vaccinated (matched) or unvaccinated (unmatched), with microchips validating classifications. From 534 classified dogs (251 vaccinated, 283 unvaccinated), the application specificity was 98.9% and sensitivity 76.2%, with positive and negative predictive values of 98.4% and 82.8% respectively. The facial recognition algorithm correctly matched 249 (99.2%) vaccinated and microchipped dogs (true positives) and failed to match two (0.8%) vaccinated dogs (false negatives). Operators correctly identified 186 (74.1%) vaccinated dogs (true positives), and 280 (98.9%) unvaccinated dogs (true negatives), but incorrectly classified 58 (23.1%) vaccinated dogs as unmatched (false negatives). Reduced application sensitivity resulted from poor quality photos and light-associated color distortion. With development and operator training, this technology has potential to be a useful tool to identify dogs and support research and intervention programs.

医療・健康
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