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Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN
Research article (Scientific Reports, 2022) · cited 75× · AI/ML
Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN
Summary
Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN is a scholarly article[1].
Key Facts
Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN's instance of is recorded as scholarly article[2].
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BibTeX@misc{4ortxyz_accurate-and-rapid-prediction-of-tuberculosis-drug-resistance-from-genome-sequence-data-using-traditional-machine-learni_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN}}, year = {2026}, url = {https://4ort.xyz/entity/accurate-and-rapid-prediction-of-tuberculosis-drug-resistance-from-genome-sequence-data-using-traditional-machine-learni}, note = {Accessed: 2026-05-24}}
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