{"id":"W4305056839","doi":"10.1117/12.2640989","title":"Malaria cell classification with residual neural network","year":2022,"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":"University of Toronto","funders":"","keywords":"Malaria; Convolutional neural network; Artificial intelligence; Residual neural network; Computer science; Transfer of learning; Pattern recognition (psychology); Diagnosis of malaria; Residual; Artificial neural network; Blood smear; Deep learning; Machine learning; Plasmodium falciparum; Biology; Immunology; Algorithm","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":[0.0003917722,0.0008033296,0.0006008619,0.0007621715,0.0002118442,0.0004710729,0.0008821856,0.0007445428,0.001580056],"category_scores_gemma":[0.0007830011,0.000192218,0.000552355,0.0005082069,0.000197738,0.000415108,0.000419895,0.0006888775,0.0008298205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007199236,"about_ca_system_score_gemma":0.0005445134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009446283,"about_ca_topic_score_gemma":0.006891319,"domain_scores_codex":[0.9997957,0.00002329267,0.00001250553,0.00005850774,0.00004949375,0.00006052211],"domain_scores_gemma":[0.9997788,0.00004324744,0.00002439952,0.00002324252,0.0001139665,0.00001634025],"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":[0.001004067,0.0004127775,0.0131567,0.0001491363,0.0001538533,0.0004630283,0.00008662301,0.3370474,0.04194559,0.001872855,0.02492608,0.578782],"study_design_scores_gemma":[0.00001165888,0.00006765946,0.001468017,0.000007187638,0.00001578658,0.00005426754,0.00001445197,0.9886536,0.007983136,0.000613815,0.001100507,0.000009867576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5126468,0.003564924,0.4642929,0.001450737,0.0005906498,0.0002658973,0.00261004,0.007207081,0.00737091],"genre_scores_gemma":[0.9034059,0.0005634524,0.08362076,0.0003584301,0.0001376342,0.0001306352,0.003653263,0.00007199488,0.008057875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009446283,"threshold_uncertainty_score":0.01878262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503761458807757,"score_gpt":0.2096797100978606,"score_spread":0.194642095509783,"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."}}