Doctor’s Handwritten Prescription BD dataset

🔗 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, "A Deep Neural Network Approach with Pioneering Local Dataset to Recognize Doctor's Handwritten Prescription in Bangladesh," 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.🔗 本数据集曾应用于以下学术出版物： A. R. Mia、M. A.-A.-S. Chowdhury、A. A. Mamun、A. M. Ruddra与N. T. Tanny，题为《孟加拉国医生手写处方识别：基于开创性本地数据集的深度神经网络方法》，发表于2024年国际计算、通信、电气与智能系统前沿会议（iCACCESS），孟加拉国达卡，2024年。 DOI: 10.1109/ACCESS.2024.10499631 💊 面向机器学习的处方单词数据集 本数据集通过提取并处理处方图像构建而成，旨在为机器学习模型的教育研究与实验提供支撑，尤其适用于医疗场景下的文本识别与分类任务。 📸 数据集构建流程 为将处方图像转换为适配机器学习的结构化数据集，本研究采用了专用单词检测算法。该算法可将处方图像分割为单个单词，将数据转换为便于机器学习模型精准识别的格式。 单词分割为首要关键步骤。 所有单词均经人工筛选，仅保留药学相关术语，剔除非药物类词汇。 数据集由多名团队成员独立完成人工标注，以确保标注准确性。 📊 数据集详情 提取总单词数：4680 文件格式：Excel（.xlsx）与CSV（.csv） 药物类别数：78类 📚 包含的药物名称 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。 上述类别涵盖了孟加拉国手写处方中常见的高频处方药物名称。 🧪 应用场景 本数据集适用于以下任务： 文本分类、光学字符识别（Optical Character Recognition, OCR）、命名实体识别（Named Entity Recognition, NER）以及深度学习模型的训练与评估。 ⚠️ 注意事项：本数据集仅可免费用于教育与科研用途。