MicroBIS - An integrated AI laboratory Assistant for Bacteria and Antimicrobial Resistance Identification

dataset.zip: Contains dataset used for training classification models. enterobac_100_train_data.txt: PyBact synthetic dataset for training bacteria classification models. 2024_05_28_atlas_antibiotics.csv: Original 'Pfizer ATLAS dataset'. amr_data_long_format_no_genes.csv: Dataset for training AMR (MIC) classification models, derived from '2024_05_28_atlas_antibiotics.csv'. amr_data_long_format_no_antibiotics_preprocessed_08_24.csv: Dataset for training gene classification models, derived from '2024_05_28_atlas_antibiotics.csv'. models.zip: Contains trained classification models gene_bin_classification_best.pkl: Trained model for resistant gene classification (binary). gene_mult_classification_best.pkl: Trained model for resistant gene classification (multi-class). mic_classification_best.pkl: Trained model for MIC classification. mic_i_classification_best.pkl: Trained model for MIC interpretation classification. rf_20_panel_enterobac_100.pkl: Trained model for bacterial classification for 20 panel bio-chemical tests. rf_8_panel_enterobac_100.pkl: Trained model for bacteria classification for 8 panel bio-chemical tests.