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                <identifier>oai:data.mendeley.com/zjjtptvn6f.2</identifier>
                <datestamp>2026-08-10T14:59:07Z</datestamp>
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    <dc:creator>Rahim, Abdur</dc:creator>
    <dc:title>Doctor’s Handwritten Prescription BD dataset</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>🔗 This dataset was used in the following publication:
A. R. Mia, M. A. -A. -S. Chowdhury, A. A. Mamun, A. M. Ruddra and N. T. Tanny, &quot;A Deep Neural Network Approach with Pioneering Local Dataset to Recognize Doctor&apos;s Handwritten Prescription in Bangladesh,&quot; 2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS), Dhaka, Bangladesh, 2024.

DOI: 10.1109/ACCESS.2024.10499631
💊 Prescription Word Dataset for Machine Learning
This dataset was created by extracting and processing prescription images to support educational research and experimentation in machine learning models, particularly for text recognition and classification in healthcare contexts.

📸 Dataset Creation Process
To transform the prescription images into a structured dataset suitable for machine learning, a specialized word detection algorithm was employed. This code segmented the prescription images into individual words, converting the data into a format that facilitates accurate recognition by ML models.

Word segmentation was the first crucial step.
Each word was manually screened to retain only pharmaceutical terms.
All non-drug terms were discarded.
Manual labelling was performed by multiple team members independently to ensure accuracy.
📊 Dataset Details
Total Words Extracted: 4,680
File Format: Excel (.xlsx) and CSV (.csv)
Number of Classes (Medicines): 78
📚 Drug Names Included
Beklo, Maxima, Leptic, Esoral, Omastin, Esonix, Canazole, Fixal, Progut, Diflu, Montair, Flexilax, Maxpro, Vifas, Conaz, Fexofast, Fenadin, Telfast, Dinafex, Ritch, Renova, Flugal, Axodin, Sergel, Nexum, Opton, Nexcap, Fexo, Montex, Exium, Lumona, Napa, Azithrocin, Atrizin, Monas, Nidazyl, Metsina, Baclon, Rozith, Bicozin, Ace, Amodis, Alatrol, Napa Extend, Rivotril, Montene, Filmet, Aceta, Tamen, Bacmax, Disopan, Rhinil, Flamyd, Metro, Zithrin, Candinil, Lucan-R, Backtone, Bacaid, Etizin, Az, Romycin, Azyth, Cetisoft, Dancel, Tridosil, Nizoder, Ketoral, Ketocon, Ketotab, Ketozol, Denixil, Provair, Odmon, Baclofen, MKast, Trilock, Flexibac.

These classes represent commonly prescribed pharmaceutical names likely to appear in handwritten prescriptions.

🧪 Usage
This dataset is ideal for:

Text classification
Optical character recognition (OCR)
Named entity recognition (NER)
Deep learning model training and evaluation
⚠️ Note: This dataset is free to use for educational and research purposes only.</dc:description>
    <dc:subject>Computer Science</dc:subject>
    <dc:subject>Medicine</dc:subject>
    <dc:subject>Health Informatics</dc:subject>
    <dc:subject>Machine Learning</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/zjjtptvn6f.2</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/zjjtptvn6f.2</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:date>2026-08-10T14:59:07Z</dc:date>
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