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Using lumbar spine radiographs as input data, we trained a convolutional neural network (CNN) to predict therapeutic outcomes after lumbar TFESI in patients with lumbosacral radicular pain caused by LSS. We retrospectively recruited 193 patients for this study. The lumbar spine radiographs included anteroposterior, lateral, and bilateral (left and right) oblique views. We cut each lumbar spine radiograph image into a square shape that included the vertebra corresponding to the level at which the TFESI was performed and the vertebrae juxta below and above that level. Output data were divided into \u201cfavorable outcome\u201d (\u2265\u200950% reduction in the numeric rating scale [NRS] score at 2\u00a0months post-TFESI) and \u201cpoor outcome\u201d (&lt;\u200950% reduction in the NRS score at 2\u00a0months post-TFESI). Using these input and output data, we developed a CNN model for predicting TFESI outcomes. The area under the curve of our model was 0.920. Its accuracy was 87.2%. Our CNN model has an excellent capacity for predicting therapeutic outcomes after lumbar TFESI in patients with lumbosacral radicular pain induced by LSS.<\/jats:p>","DOI":"10.1038\/s41598-024-59288-w","type":"journal-article","created":{"date-parts":[[2024,4,11]],"date-time":"2024-04-11T16:01:51Z","timestamp":1712851311000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Convolutional neural network algorithm trained on lumbar spine radiographs to predict outcomes of transforaminal epidural steroid injection for lumbosacral radicular pain from spinal stenosis"],"prefix":"10.1038","volume":"14","author":[{"given":"Jeoung Kun","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min Cheol","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,11]]},"reference":[{"key":"59288_CR1","first-page":"337","volume":"65","author":"AS Radu","year":"1998","unstructured":"Radu, A. 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