{"id":"W4410074680","doi":"10.63471/am24003","title":"Deep Learning Models for Early Detection of Alzheimer’s Disease Using Neuroimaging Data","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Medical Sciences and Artificial Intelligence","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wycliffe College","funders":"","keywords":"Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Deep learning; Artificial intelligence; Neuroscience; Disease; Alzheimer's disease; Computer science; Psychology; Machine learning; Data science; 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":[0.001268415,0.0008700122,0.0005111405,0.001051376,0.000191312,0.000775888,0.000941176,0.0007733105,0.00126845],"category_scores_gemma":[0.00312201,0.0003443396,0.0007258084,0.0008856977,0.0002622833,0.001145376,0.0006983908,0.001475992,0.0006308275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008416461,"about_ca_system_score_gemma":0.001012191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01085445,"about_ca_topic_score_gemma":0.01256863,"domain_scores_codex":[0.9997008,0.00007396074,0.00002791184,0.0000868888,0.00006537716,0.00004505625],"domain_scores_gemma":[0.9992899,0.0003518922,0.00009623355,0.00006611241,0.0001670781,0.00002869965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003220937,0.0002550052,0.01597109,0.0002951793,0.0002889489,0.0001385636,0.0001004917,0.6584108,0.004755674,0.008512367,0.006886451,0.3040633],"study_design_scores_gemma":[0.000005754005,0.00003228577,0.001171102,0.00002841826,0.00002434016,0.00001997477,0.000009777033,0.9925042,0.0009021009,0.004339727,0.0009549817,0.00000733881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1349425,0.007866601,0.8453599,0.001999395,0.0002840956,0.0001658098,0.0031617,0.002322634,0.003897344],"genre_scores_gemma":[0.8627322,0.003797058,0.1235844,0.0003906347,0.0001422519,0.0002453866,0.004380851,0.00009958967,0.004627555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01085445,"threshold_uncertainty_score":0.02158254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2424978383686097,"score_gpt":0.4155962429471712,"score_spread":0.1730984045785616,"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."}}