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Min Si Thu
jojo-ai-mst
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đ˛đ˛ Releasing the Myanmar Tuberculosis Instruction Dataset â a MyanmarâEnglish parallel corpus for medical NLP in one of the lowest-resourced language settings in Southeast Asia. Most TB datasets are either structured clinical data or English-only research corpora. This one fills a different gap: instructional, guideline-based content in Burmese, formatted for instruction tuning and medical QA. ### What's inside - 2,043 instructionâresponse pairs - MyanmarâEnglish parallel - 7 TB domains: treatment, diagnostics, drug management, MDR-TB, infection control, patient education, healthcare worker training - Sourced from WHO guidelines, Myanmar NTP protocols, and standard medical references - MIT licensed Useful for - Fine-tuning Myanmar-language medical LLMs - TB question answering - Translation evaluation in a medical domain - General low-resource medical NLP ``` from datasets import load_dataset ds = load_dataset("jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions") ``` đ https://huggingface.co/datasets/jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions Built by Min Si Thu and Khin Myat Noe. Feedback welcome â especially from anyone working on SEA medical AI or Burmese NLP. #MedicalAI #LowResourceNLP #Myanmar #Burmese #Tuberculosis #InstructionTuning
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Burmese Language Datasets
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jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions
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