{"id":"W4292002528","doi":"10.1109/icict54344.2022.9850506","title":"Machine Learning on Web: Skin Lesion Classification using CNN","year":2022,"lang":"en","type":"article","venue":"2022 International Conference on Inventive Computation Technologies (ICICT)","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Convolutional neural network; Upload; Artificial intelligence; Skin lesion; Contextual image classification; Seborrheic keratosis; Skin cancer; Lesion; Artificial neural network; Pattern recognition (psychology); Machine learning; Dermatology; Image (mathematics); Cancer; World Wide Web; Medicine; Pathology","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":[0.0003146926,0.0006514312,0.0003523264,0.001090944,0.0001746034,0.0006294843,0.0007425811,0.00056611,0.0047255],"category_scores_gemma":[0.0007740813,0.0002159062,0.000511587,0.0009323401,0.0001331004,0.0007170847,0.0005016013,0.0004831789,0.002224586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005539797,"about_ca_system_score_gemma":0.000342086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00975194,"about_ca_topic_score_gemma":0.01058881,"domain_scores_codex":[0.9997737,0.00002431466,0.00001089788,0.00006105167,0.00007574366,0.00005434461],"domain_scores_gemma":[0.9998412,0.00003405725,0.00001600714,0.00003790787,0.00005718875,0.00001362551],"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":[0.0002688618,0.0003290201,0.008729273,0.0001943412,0.0001485774,0.0003488267,0.00004152361,0.06537814,0.01912443,0.002007493,0.03142899,0.8720005],"study_design_scores_gemma":[0.00001407376,0.00008662299,0.006481455,0.00003863062,0.0000364325,0.0002712556,0.00003640342,0.9626095,0.01904164,0.002605639,0.008757072,0.00002126437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2556304,0.005844757,0.6645714,0.001184569,0.000800269,0.0005104182,0.008898996,0.03138505,0.03117421],"genre_scores_gemma":[0.7900322,0.001982228,0.1742502,0.0005030811,0.0002240916,0.0002871463,0.01177332,0.000376195,0.02057158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00975194,"threshold_uncertainty_score":0.01939034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1125321441523557,"score_gpt":0.3358395635517378,"score_spread":0.2233074193993821,"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."}}