{"672491":{"#nid":"672491","#data":{"type":"external_news","title":"Diagnosing the \u201cSilent Killer\u201d: AI Tackles Early Stage Ovarian Cancer","body":[{"value":"\u003Cp\u003EA major bottleneck in early detection is the molecular heterogeneity between ovarian cancer (OC) patients, which limits the likelihood of identifying individual biomarkers that are shared among patients. In a new study \u201c\u003Ca href=\u0022https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0090825823016360\u0022\u003EA personalized probabilistic approach to ovarian cancer diagnostics\u003C\/a\u003E,\u201d published in\u0026nbsp;\u003Cem\u003EGynecologic Oncology,\u0026nbsp;\u003C\/em\u003Eresearchers from Georgia Tech have addressed this challenge by applying machine learning (ML) on patient metabolic profiles to identify biomarker patterns for personalized OC diagnosis. The Georgia Tech researchers include \u003Ca href=\u0022https:\/\/biosciences.gatech.edu\/people\/john-mcdonald\u0022\u003EJohn McDonald\u003C\/a\u003E, Professor Emeritus, \u003Ca href=\u0022https:\/\/biosciences.gatech.edu\u0022\u003ESchool of Biological Sciences\u003C\/a\u003E;\u0026nbsp;\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/dongjo-ban\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDongjo Ban\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, a Bioinformatics Ph.D. student in McDonald\u2019s lab; Research Scientists\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/cos.gatech.edu\/news\/postdoctoral-scientist-named-first-mccallum-early-career-fellow\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EStephen N. Housley\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E,\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/lilya-matyunina\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ELilya V. Matyunina\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, and\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/l-deette-walker\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EL.DeEtte (Walker) McDonald\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E; and Regents\u2019 Professor\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/biosciences.gatech.edu\/people\/jeffrey-skolnick\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EJeffrey Skolnick\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, who also serves as Mary and Maisie Gibson Chair in the School of Biological Sciences and Georgia Research Alliance Eminent Scholar in Computational Systems Biology.\u0026nbsp;(The study was also covered at \u003Ca href=\u0022https:\/\/nypost.com\/2024\/01\/29\/lifestyle\/new-test-detects-ovarian-cancer-earlier-thanks-to-ai\/\u0022\u003EThe New York Post\u003C\/a\u003E, \u003Ca href=\u0022https:\/\/www.technologynetworks.com\/proteomics\/news\/diagnostic-test-detects-ovarian-cancer-with-93-accuracy-383283\u0022\u003ETechnology Networks,\u003C\/a\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/medicalxpress.com\/news\/2024-01-leverage-ai-early-diagnostic-ovarian.html\u0022\u003EMedical Xpress\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.news-medical.net\/news\/20240129\/Machine-learning-unlocks-personalized-approach-to-early-ovarian-cancer-detection.aspx\u0022\u003ENews-Medical.net\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.medscape.com\/viewarticle\/two-step-strategy-improves-early-stage-ovarian-cancer-2024a10001sq\u0022\u003EMedscape\u003C\/a\u003E\u0026nbsp;and \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/www.diagnosticsworldnews.com\/news\/2024\/03\/19\/trial-begins-for-probabilistic-approach-to-diagnosing-ovarian-cancer\u0022\u003EDiagnostics World\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E.)\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EA major bottleneck in early detection is the molecular heterogeneity between ovarian cancer (OC) patients, which limits the likelihood of identifying individual biomarkers that are shared among patients. In a new study \u201c\u003Ca href=\u0022https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0090825823016360\u0022\u003EA personalized probabilistic approach to ovarian cancer diagnostics\u003C\/a\u003E,\u201d published in\u0026nbsp;\u003Cem\u003EGynecologic Oncology,\u0026nbsp;\u003C\/em\u003Eresearchers from Georgia Tech have addressed this challenge by applying machine learning (ML) on patient metabolic profiles to identify biomarker patterns for personalized OC diagnosis. The Georgia Tech researchers include \u003Ca href=\u0022https:\/\/biosciences.gatech.edu\/people\/john-mcdonald\u0022\u003EJohn McDonald\u003C\/a\u003E, Professor Emeritus, \u003Ca href=\u0022https:\/\/biosciences.gatech.edu\u0022\u003ESchool of Biological Sciences\u003C\/a\u003E;\u0026nbsp;\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/dongjo-ban\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDongjo Ban\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, a Bioinformatics Ph.D. student in McDonald\u2019s lab; Research Scientists\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/cos.gatech.edu\/news\/postdoctoral-scientist-named-first-mccallum-early-career-fellow\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EStephen N. Housley\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E,\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/lilya-matyunina\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ELilya V. Matyunina\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, and\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/mcdonaldlab.biology.gatech.edu\/l-deette-walker\/\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EL.DeEtte (Walker) McDonald\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E; and Regents\u2019 Professor\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/biosciences.gatech.edu\/people\/jeffrey-skolnick\u0022\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EJeffrey Skolnick\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E, who also serves as Mary and Maisie Gibson Chair in the School of Biological Sciences and Georgia Research Alliance Eminent Scholar in Computational Systems Biology.\u0026nbsp;(The study was also covered at \u003Ca href=\u0022https:\/\/nypost.com\/2024\/01\/29\/lifestyle\/new-test-detects-ovarian-cancer-earlier-thanks-to-ai\/\u0022\u003EThe New York Post\u003C\/a\u003E, \u003Ca href=\u0022https:\/\/www.technologynetworks.com\/proteomics\/news\/diagnostic-test-detects-ovarian-cancer-with-93-accuracy-383283\u0022\u003ETechnology Networks,\u003C\/a\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/medicalxpress.com\/news\/2024-01-leverage-ai-early-diagnostic-ovarian.html\u0022\u003EMedical Xpress\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.news-medical.net\/news\/20240129\/Machine-learning-unlocks-personalized-approach-to-early-ovarian-cancer-detection.aspx\u0022\u003ENews-Medical.net\u003C\/a\u003E,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.medscape.com\/viewarticle\/two-step-strategy-improves-early-stage-ovarian-cancer-2024a10001sq\u0022\u003EMedscape\u003C\/a\u003E\u0026nbsp;and \u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Ca href=\u0022https:\/\/www.diagnosticsworldnews.com\/news\/2024\/03\/19\/trial-begins-for-probabilistic-approach-to-diagnosing-ovarian-cancer\u0022\u003EDiagnostics World\u003C\/a\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E.)\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":"","uid":"34434","created_gmt":"2024-01-26 20:52:00","changed_gmt":"2024-04-11 14:42:14","author":"Renay San Miguel","boilerplate_text":"","field_publication":"","publication":"Inside Precision Medicine","field_article_url":"","publication_url":"https:\/\/www.insideprecisionmedicine.com\/topics\/oncology\/diagnosing-the-silent-killer-ai-tackles-early-stage-ovarian-cancer\/","dateline":{"date":"2024-01-26T00:00:00-05:00","iso_date":"2024-01-26T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"groups":[{"id":"1278","name":"College of Sciences"},{"id":"1275","name":"School of Biological Sciences"}],"categories":[{"id":"146","name":"Life Sciences and Biology"},{"id":"135","name":"Research"},{"id":"134","name":"Student and Faculty"}],"keywords":[{"id":"4896","name":"College of Sciences"},{"id":"166882","name":"School of Biological Sciences"},{"id":"2371","name":"John McDonald"},{"id":"11937","name":"Jeffrey Skolnick"},{"id":"193449","name":"Dongjo Ban"},{"id":"193450","name":"Stephen N. Housley"},{"id":"193451","name":"Lilya Matyunina"},{"id":"193452","name":"L. DeEtte McDonald"},{"id":"2372","name":"ovarian cancer"},{"id":"189331","name":"diagnostic testing"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}