{"id":2834,"date":"2023-11-30T01:46:00","date_gmt":"2023-11-29T14:46:00","guid":{"rendered":"https:\/\/harrison.ai\/?p=2834"},"modified":"2025-10-04T20:05:38","modified_gmt":"2025-10-04T10:05:38","slug":"consecutive-cohort-analysis-with-nlp-and-multi-finding-ai-algorithm-for-chest-radiographs-multidimensional-opportunity-for-qa-qc","status":"publish","type":"post","link":"https:\/\/harrison.ai\/consecutive-cohort-analysis-with-nlp-and-multi-finding-ai-algorithm-for-chest-radiographs-multidimensional-opportunity-for-qa-qc\/","title":{"rendered":"Consecutive cohort analysis with NLP and multi-finding AI algorithm for chest radiographs: Multidimensional opportunity for QA\/QC."},"content":{"rendered":"    <section id=\"evidence-block-block_55ba9fbff915d671842d94ef6b426e12\" class=\"study-block   text-\" >\n        <div class=\"container  container--tab\">\n            <div class=\"container container--tab\">\n                <div class=\"connect__decor hide-md\">\n                    <span class=\"pixel-decor\" style=\"background-color: rgba(9, 114, 241, 0.75)\"><\/span>\n                    <span class=\"pixel-decor\" style=\"background-color: #0972f1\"><\/span>\n                    <span class=\"pixel-decor\" style=\"background-color: rgba(9, 114, 241, 0.5)\"><\/span>\n                    <span class=\"pixel-decor hide-sm\" style=\"background-color: rgba(9, 114, 241, 0.5)\"><\/span>\n                <\/div>\n                <div class=\"study__share hide-sm\" data-aos=\"fade-up\">\n                                    <\/div>\n                <div class=\"study__row\">\n                    <div class=\"study__left\" data-aos=\"fade-up\"><\/div>\n                    <div class=\"study__right\" data-aos=\"fade-up\">\n                        <div class=\"text b1\">\n                        <h5>Author<\/h5>\n<p>Garza Frias, Emiliano | Mass General Brigham, US<\/p>\n<p>Scientific poster presentation (<span class=\"TextRun Highlight SCXW101419674 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW101419674 BCX0\">W5B-SPCH-4<\/span><\/span>) at RSNA 2023, 26 \u2013 30. November 2023 in Chicago, US<\/p>\n                        <\/div>\n                                            <\/div>\n                <\/div>\n                                                            <div class=\"study__row\">\n                            <div class=\"study__left\" data-aos=\"fade-up\">\n                                <h2 class=\"h5\">Purpose<\/h2>\n                            <\/div>\n                            <div class=\"study__right\" data-aos=\"fade-up\">\n                                <div class=\"text b1\"><p><span class=\"TextRun Highlight SCXW41445805 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW41445805 BCX0\"><span class=\"TextRun Highlight SCXW157394616 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW157394616 BCX0\">Are consecutive cohort analyses with NLP and comprehensive decision-support AI for CXR a valid tool for quality control?<\/span><\/span><\/span><\/span><\/p>\n<\/div>                            <\/div>\n                        <\/div>\n                                            <div class=\"study__row\">\n                            <div class=\"study__left\" data-aos=\"fade-up\">\n                                <h2 class=\"h5\">Method<\/h2>\n                            <\/div>\n                            <div class=\"study__right\" data-aos=\"fade-up\">\n                                <div class=\"text b1\"><p><span class=\"TextRun Highlight SCXW117106848 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW117106848 BCX0\"><span class=\"TextRun Highlight SCXW149223298 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW149223298 BCX0\">NLP-based radiology reports search <\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">was performed on <\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">3,760 adult CXR studies<\/span><span class=\"NormalTextRun SCXW149223298 BCX0\"> and compared with the result of a comprehensive AI <\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">algorithm <\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">for chest X-<\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">r<\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">ay (annalise.ai)<\/span><span class=\"NormalTextRun SCXW149223298 BCX0\">.<\/span><\/span><\/span><\/span><\/p>\n<\/div>                            <\/div>\n                        <\/div>\n                                            <div class=\"study__row\">\n                            <div class=\"study__left\" data-aos=\"fade-up\">\n                                <h2 class=\"h5\">Results<\/h2>\n                            <\/div>\n                            <div class=\"study__right\" data-aos=\"fade-up\">\n                                <div class=\"text b1\"><p><span class=\"TextRun Highlight SCXW244850336 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW244850336 BCX0\"><span class=\"NormalTextRun SCXW120603525 BCX0\">NLP<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\"> extracted reports and AI <\/span><span class=\"NormalTextRun SCXW120603525 BCX0\">output<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\"> showed <\/span><span class=\"NormalTextRun SCXW120603525 BCX0\">high levels<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\"> of concordance<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\">. The AI model showed <\/span><span class=\"NormalTextRun SCXW120603525 BCX0\">good performance<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\"> at detecting over- and <\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW120603525 BCX0\">undercalls<\/span><span class=\"NormalTextRun SCXW120603525 BCX0\">.<\/span><\/span><\/span><\/p>\n<\/div>                            <\/div>\n                        <\/div>\n                                            <div class=\"study__row\">\n                            <div class=\"study__left\" data-aos=\"fade-up\">\n                                <h2 class=\"h5\">Key Takeaway<\/h2>\n                            <\/div>\n                            <div class=\"study__right\" data-aos=\"fade-up\">\n                                <div class=\"text b1\"><p><span class=\"TextRun Highlight SCXW184445990 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW184445990 BCX0\"><span class=\"TextRun Highlight SCXW90001834 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW90001834 BCX0\">NLP<\/span><span class=\"NormalTextRun SCXW90001834 BCX0\"> and <\/span><span class=\"NormalTextRun SCXW90001834 BCX0\">comprehensive <\/span><span class=\"NormalTextRun SCXW90001834 BCX0\">AI discrepancy analysis can be <\/span><span class=\"NormalTextRun SCXW90001834 BCX0\">a valuable<\/span> <span class=\"NormalTextRun SCXW90001834 BCX0\">approach<\/span> <span class=\"NormalTextRun SCXW90001834 BCX0\">to<\/span><span class=\"NormalTextRun SCXW90001834 BCX0\"> quality assessment and control.<\/span><\/span><\/span><\/span><\/p>\n<p>&nbsp;<\/p>\n<\/div>                            <\/div>\n                        <\/div>\n                                            <div class=\"study__row\">\n                            <div class=\"study__left\" data-aos=\"fade-up\">\n                                <h2 class=\"h5\">Disclaimer<\/h2>\n  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