VetAce – A Deep Learning Inspired Framework for Classification and Prediction of Pet Diseases

During the period of the COVID-19 pandemic, we noticed a situation of lockdown, when the epidemic outbreak was at its peak. In those circumstances, the illness of pets and getting it diagnoses was a major worry for humans. In this study, we proposed an advanced technological web-based solution to tackle such a bad situation. We have introduced the concept of using a Convolutional Neural Network (CNN) and transfer learning for predicting and classifying the common disease of pets by uploading their visuals. The proposed framework achieved high accuracy (89%), precision (92%), specificity (74.5%), and sensitivity (75%) for pet disease prediction and breed classification which outperforms all other considered state-of-art algorithms (ANN, RNN, and CNN). Further, this online diagnosing framework will help humans by providing insights into the common causes of pet diseases. Additionally, it will also specify the prevailing preventive measures and medical recommendations to cure the pet.