{"doi":"10.1007/s10278-024-01336-y","title":"ViViEchoformer: Deep Video Regressor Predicting Ejection Fraction","abstract":"Abstract Heart disease is the leading cause of death worldwide, and cardiac function as measured by ejection fraction (EF) is an important determinant of outcomes, making accurate measurement a critical parameter in PT evaluation. Echocardiograms are commonly used for measuring EF, but human interpretation has limitations in terms of intra- and inter-observer (or reader) variance. Deep learning (DL) has driven a resurgence in machine learning, leading to advancements in medical applications. We introduce the ViViEchoformer DL approach, which uses a video vision transformer to directly regress the left ventricular function (LVEF) from echocardiogram videos. The study used a dataset of 10,030 apical-4-chamber echocardiography videos from patients at Stanford University Hospital. The model accurately captures spatial information and preserves inter-frame relationships by extracting spatiotemporal tokens from video input, allowing for accurate, fully automatic EF predictions that aid human assessment and analysis. The ViViEchoformer’s prediction of ejection fraction has a mean absolute error of 6.14%, a root mean squared error of 8.4%, a mean squared log error of 0.04, and an $${R}^{2}$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:msup> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:math> of 0.55. ViViEchoformer predicted heart failure with reduced ejection fraction (HFrEF) with an area under the curve of 0.83 and a classification accuracy of 87 using a standard threshold of less than 50% ejection fraction. Our video-based method provides precise left ventricular function quantification, offering a reliable alternative to human evaluation and establishing a fundamental basis for echocardiogram interpretation.","journal":"Journal of Imaging Informatics in Medicine","year":2024,"id":449616,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9557,"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":1160055,"name":"Sait Alp","orcid":"0000-0003-2462-6166","position":1,"is_corresponding":false},{"id":291378,"name":"Md. Shenuarin Bhuiyan","orcid":"0000-0003-0073-3071","position":2,"is_corresponding":false},{"id":1269394,"name":"Tarek Helmy","orcid":"0000-0002-3386-4302","position":3,"is_corresponding":false},{"id":344652,"name":"A. Wayne Orr","orcid":"0000-0002-2377-213X","position":4,"is_corresponding":false},{"id":1269899,"name":"Md. Mostafizur Rahman Bhuiyan","orcid":null,"position":5,"is_corresponding":false},{"id":295505,"name":"Steven A. Conrad","orcid":"0000-0002-4014-969X","position":6,"is_corresponding":false},{"id":301633,"name":"John A. Vanchiere","orcid":"0000-0001-6863-4323","position":8,"is_corresponding":false},{"id":226777,"name":"Christopher G. Kevil","orcid":"0000-0003-0863-7260","position":9,"is_corresponding":false},{"id":267885,"name":"Mohammad Alfrad Nobel Bhuiyan","orcid":"0000-0002-6011-2624","position":10,"is_corresponding":false},{"id":1160054,"name":"Taymaz Akan","orcid":"0000-0003-4070-1058","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:02:20.585759Z","pmid":"39586913","pmcid":null,"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":[]}