{"id":"W4387251285","doi":"10.1109/aic57670.2023.10263933","title":"Automatic White Blood Cell Classification Using Convolutional Neural Network","year":2023,"lang":"en","type":"article","venue":"","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Convolutional neural network; Overfitting; Computer science; Artificial intelligence; Pattern recognition (psychology); White blood cell; Peripheral blood; Deep learning; Feature extraction; Anemia; Artificial neural network; Machine learning; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003255355,0.0007269689,0.0004626402,0.001066279,0.0002129537,0.0005225206,0.0007302538,0.0005585534,0.001060975],"category_scores_gemma":[0.0006094298,0.0002014904,0.0004266874,0.0006336334,0.0001606066,0.0004125632,0.0003859225,0.0005488764,0.0006461574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007907543,"about_ca_system_score_gemma":0.0006945993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01791718,"about_ca_topic_score_gemma":0.01967589,"domain_scores_codex":[0.9998142,0.00001616634,0.00001120533,0.00005982507,0.00005425428,0.00004439365],"domain_scores_gemma":[0.9997985,0.00004030876,0.00002903193,0.00002126348,0.0000962773,0.0000146143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006178571,0.0003525849,0.02064949,0.0001287999,0.0001575793,0.0004182705,0.00004694845,0.1067075,0.07694933,0.001705901,0.01896911,0.7732967],"study_design_scores_gemma":[0.000009477048,0.00003024828,0.00361374,0.00001162506,0.00002356765,0.00009624671,0.000006893003,0.9783346,0.01558516,0.0006290941,0.001647217,0.00001208777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3745769,0.005001724,0.5962678,0.0009920115,0.0004863711,0.0001772201,0.003331614,0.0110581,0.008108347],"genre_scores_gemma":[0.8781071,0.001332391,0.1045962,0.0003753153,0.0001274835,0.00009198076,0.004940551,0.0001148741,0.0103141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01791718,"threshold_uncertainty_score":0.03562582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03760237403897718,"score_gpt":0.2581706693709998,"score_spread":0.2205682953320226,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}