{"doi":"10.1167/tvst.13.8.11","title":"Transformer-Based Deep Learning Prediction of 10-Degree Humphrey Visual Field Tests From 24-Degree Data","abstract":"Purpose: To predict 10-2 Humphrey visual fields (VFs) from 24-2 VFs and associated non-total deviation features using deep learning. Methods: We included 5189 reliable 24-2 and 10-2 VF pairs from 2236 patients, and 28,409 reliable pairs of macular OCT scans and 24-2 VF from 19,527 eyes of 11,560 patients. We developed a transformer-based deep learning model using 52 total deviation values and nine VF test features to predict 68 10-2 total deviation values. The mean absolute error, root mean square error, and the R2 were evaluation metrics. We further evaluated whether the predicted 10-2 VFs can improve the structure-function relationship between macular thinning and paracentral VF loss in glaucoma. Results: The average mean absolute error and R2 for 68 10-2 VF test points were 3.30 ± 0.52 dB and 0.70 ± 0.11, respectively. The accuracy was lower in the inferior temporal region. The model placed greater emphasis on 24-2 VF points near the central fixation point when predicting the 10-2 VFs. The inclusion of nine VF test features improved the mean absolute error and R2 up to 0.17 ± 0.06 dB and 0.01 ± 0.01, respectively. Age was the most important 24-2 VF test parameter for 10-2 VF prediction. The predicted 10-2 VFs achieved an improved structure-function relationship between macular thinning and paracentral VF loss, with the R2 at the central 4, 12, and 16 locations of 24-2 VFs increased by 0.04, 0.05 and 0.05, respectively (P < 0.001). Conclusions: The 10-2 VFs may be predicted from 24-2 data. Translational Relevance: The predicted 10-2 VF has the potential to improve glaucoma diagnosis.","journal":"Translational Vision Science & Technology","year":2024,"id":449044,"datarank":0.33422782077042534,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.06546390038621705,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.06546390038621705,"corpus_percentile":48.21691034269359,"corpus_rank":6695,"citation_count":5,"citer_count":5,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5651,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":905967,"name":"Anagha Lokhande","orcid":"0000-0002-1498-6427","position":1,"is_corresponding":false},{"id":1080893,"name":"Yu Tian","orcid":"0000-0001-5533-7506","position":2,"is_corresponding":false},{"id":525149,"name":"Yan Luo","orcid":"0000-0002-5830-1936","position":3,"is_corresponding":false},{"id":1268394,"name":"M. Eslami","orcid":"0000-0002-9246-5328","position":4,"is_corresponding":false},{"id":1122487,"name":"Saber Kazeminasab","orcid":"0000-0002-7238-4942","position":5,"is_corresponding":false},{"id":259255,"name":"Tobias Elze","orcid":"0000-0002-2032-0496","position":6,"is_corresponding":false},{"id":342306,"name":"Lucy Q. Shen","orcid":"0000-0002-0360-1296","position":7,"is_corresponding":false},{"id":6895,"name":"Louis R. Pasquale","orcid":"0000-0002-5835-3496","position":8,"is_corresponding":false},{"id":343407,"name":"Sarah R. Wellik","orcid":null,"position":9,"is_corresponding":false},{"id":342308,"name":"Carlos Gustavo De Moraes","orcid":"0000-0002-5626-0894","position":10,"is_corresponding":false},{"id":342309,"name":"Jonathan S. Myers","orcid":"0000-0002-8251-6750","position":11,"is_corresponding":false},{"id":644341,"name":"Nazlee Zebardast","orcid":"0000-0003-1763-9401","position":12,"is_corresponding":false},{"id":875588,"name":"David Friedman","orcid":null,"position":13,"is_corresponding":false},{"id":282244,"name":"Michael V. Boland","orcid":"0000-0003-2506-7095","position":14,"is_corresponding":false},{"id":342311,"name":"Mengyu Wang","orcid":"0000-0002-7188-7126","position":15,"is_corresponding":false},{"id":597429,"name":"Min Shi","orcid":"0009-0003-0238-6306","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":null,"created_at":"2026-07-19T02:02:16.291892Z","pmid":"39110574","pmcid":"PMC11316452","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}