التفاصيل البيبلوغرافية
| العنوان: |
Using AI to detect breeding-related brain and airway disorders in pedigree dogs |
| المؤلفون: |
Cumber, Jake, Taghipour-Gorjikolaie, Mehran, Rusbridge, Clare, Wells, Kevin |
| بيانات النشر: |
Zenodo |
| سنة النشر: |
2023 |
| المجموعة: |
Zenodo |
| مصطلحات موضوعية: |
Chiari-like malformation, Syringomyelia, Machine learning, Spherical harmonics, Medical Imaging, Veterinary medicine |
| الوصف: |
Covid-19 lockdowns dramatically accelerated demand for companion family animals. But increased selective breeding of flat-faced dogs has led to a crisis in associated neurological, skeletal, and airway disorders, where canine quality of life is inadvertently sacrificed for cuteness in appearance. It is suggested that some physical traits are more likely to be found in pedigree dogs afflicted with several genetic developmental disorders, and the exaggeration of these traits worsen the severity of such disorders. However, identifying and grading these traits is impractical without large-scale medical imaging and invasive surgical procedures. A database comprising CT scans obtained from Cavalier King Charles Spaniels was provided to this study, from which cranial models can be generated with computer vision software. A novel low-cost AI methodology has been developed to identify key physical characteristics, present in crania, associated with genetic developmental diseases affecting the Cavalier. Early AI-led results found a significant bulge on the top of the skull linked to neurological disease with near-perfect sensitivity. Continuing developments of this methodology will assist breeders to better develop sustainable, ethical breeding practices for at-risk pedigree dogs and contribute to reducing quality of life issues arising from genetic developmental disorders. |
| نوع الوثيقة: |
conference object |
| اللغة: |
unknown |
| Relation: |
https://zenodo.org/communities/makingtheinvisiblevisible23; https://doi.org/10.5281/zenodo.8005787; https://doi.org/10.5281/zenodo.8005788; oai:zenodo.org:8005788 |
| DOI: |
10.5281/zenodo.8005788 |
| الاتاحة: |
https://doi.org/10.5281/zenodo.8005788 |
| Rights: |
info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: |
edsbas.B7C8AAFF |
| قاعدة البيانات: |
BASE |