The Pharmaceutical Drug Classification using Deep Learning Approaches
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Keywords:
CNN, Inception ResNetV2, VGG19, Deep Learning, Drug ClassificationAbstract
Accurate drug classification through deep learning approaches enhance medication safety by
minimizing errors in drug identification and dosage, ultimately safeguarding patient health. These advanced
techniques provide a promising solution to prevent the risks associated with incorrect medication use,
ensuring that patients receive the most effective treatment for their condition. Patients may face serious
consequences due to improper medication use, including errors in taking the wrong drug or incorrect
dosage. In order to mitigate the risk of human error in identifying medications, we employed advanced deep
learning models such as Convolutional Neural Networks (CNN), VGG19, and Inception-ResNetV2. These
models were trained using a comprehensive dataset comprising over 7000 labeled drug images. Through
our study, we achieved a remarkable validation accuracy of 95\% utilizing the CNN model. This
demonstrates the potential effectiveness of employing deep learning techniques in accurately classifying
drug images, thereby reducing the likelihood of medication errors and improving patient safety.
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References
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Drug image dataset is openly accessible on Kaggle: https://www.kaggle.com/datasets/gauravduttakiit/pharmaceutical-drug-recognition
