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Pill Identification Model Using Deep Learning Techniques

  • Unique Paper ID: 164868
  • Volume: 10
  • Issue: 12
  • PageNo: 2705-2706
  • Abstract:
  • Since accurate drug identification immediately affects patient care and avoids serious repercussions, it is essential to prevent medical errors. Patients run a significant risk of injury and consequences when they misuse medications. Healthcare workers are burdened by this problem because, in situations where patients are unable to supply their prescription information, they must manually search through pill databases to identify drugs. The development of computerized medication systems that use information technology to precisely identify medications and identify possible interactions between them is urgently needed to address these issues. The MobileNet architecture serves as the foundational paradigm for the system, which is created in Python. The principal aim of this project is to identify medications intelligently and recognize pills accurately from photos. In order to achieve this, 1,268 samples from the dataset are used to train and test the system. The system achieves excellent performance metrics through its training process, which makes use of the MobileNet architecture. Both the validation accuracy and the training accuracy that were attained are reported as 98.00%. The system's capacity to precisely identify medicinal medications and detect pills is validated by the excellent accuracy rates. This pill identification system reduces human error and saves healthcare worker’s important time by automating the pill identification procedure. The technology also helps patients, as it allows them to confirm that they are taking their prescribed medications and obtain detailed pharmacological information.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 2705-2706

Pill Identification Model Using Deep Learning Techniques

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Journal no 47859

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