{"id":"W3175485607","doi":"10.22214/ijraset.2021.35234","title":"A Novel Deep Convolutional Neural Network for Tuberculosis Detection","year":2021,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tuberculosis; Mycobacterium tuberculosis; Convolutional neural network; Quarter (Canadian coin); Artificial intelligence; Deep learning; Artificial neural network; Medicine; Computer science; Machine learning; Environmental health; Geography; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003292104,0.000543968,0.0004405241,0.0004110695,0.0003016378,0.0005003392,0.000885669,0.000876086,0.001670538],"category_scores_gemma":[0.00056871,0.0002544854,0.0004285484,0.0004067222,0.0001877353,0.0005804241,0.0005358584,0.0007457873,0.0006306208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007709402,"about_ca_system_score_gemma":0.000966257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01301339,"about_ca_topic_score_gemma":0.01723211,"domain_scores_codex":[0.9998407,0.00001648448,0.000008772175,0.00004514644,0.00004774307,0.00004094901],"domain_scores_gemma":[0.9998387,0.00004366205,0.00001622594,0.00001382473,0.00007006047,0.00001754278],"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":[0.0005549029,0.0004130815,0.008420857,0.0002068667,0.0001815337,0.0004299926,0.00006199873,0.2320773,0.04237709,0.006072571,0.01677252,0.6924313],"study_design_scores_gemma":[0.00000823062,0.00005000102,0.0007971433,0.00001057109,0.00002027095,0.00008436695,0.000005007057,0.9923563,0.004124131,0.0007238372,0.001811573,0.000008430434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1094494,0.005214459,0.8646407,0.001571149,0.0007278046,0.0001065364,0.001154035,0.003969945,0.01316599],"genre_scores_gemma":[0.8026128,0.001799939,0.1709866,0.0009430178,0.0002135028,0.0000967139,0.001668727,0.00006364114,0.02161509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01301339,"threshold_uncertainty_score":0.02587527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06385846181813058,"score_gpt":0.400131510128983,"score_spread":0.3362730483108524,"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."}}