{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T14:38:06Z","timestamp":1781275086420,"version":"3.54.1"},"reference-count":96,"publisher":"Georg Thieme Verlag KG","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Am J Perinatol"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Pregnancies impacted by diabetes face the compounded challenge of strict glycemic control with mounting insulin resistance as the pregnancy progresses. New technological advances, including artificial intelligence (AI) and the Internet of Medical Things (IoMT), are revolutionizing health care delivery by providing innovative solutions for diabetes care during pregnancy. Together, AI and the IoMT are a multibillion-dollar industry that integrates advanced medical devices and sensors into a connected network that enables continuous monitoring of glucose levels. AI-driven clinical decision support systems (CDSSs) can predict glucose trends and provide tailored evidence-based treatments with real-time adjustments as insulin resistance changes with placental growth. Additionally, mobile health (mHealth) applications facilitate patient education and self-management through real-time tracking of diet, physical activity, and glucose levels. Remote monitoring capabilities are particularly beneficial for pregnant persons with diabetes as they extend quality care to underserved populations and reduce the need for frequent in-person visits. This high-resolution monitoring allows physicians and patients access to an unprecedented wealth of data to make more informed decisions based on real-time data, reducing complications for both the mother and fetus. These technologies can potentially improve maternal and fetal outcomes by enabling timely, individualized interventions based on personalized health data. While AI and IoMT offer significant promise in enhancing diabetes care for improved maternal and fetal outcomes, their implementation must address challenges such as data security, cost-effectiveness, and preserving the essential patient\u2013provider relationship.<\/jats:p>","DOI":"10.1055\/a-2489-4462","type":"journal-article","created":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T19:14:51Z","timestamp":1732648491000},"page":"1540-1549","source":"Crossref","is-referenced-by-count":5,"title":["Innovations in Diabetes Management for Pregnant Women: Artificial Intelligence and the Internet of Medical Things"],"prefix":"10.1055","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9882-0936","authenticated-orcid":false,"given":"Ellen M.","family":"Murrin","sequence":"additional","affiliation":[{"name":"Inova Fairfax Medical Campus, Falls Church, Virginia"},{"name":"Department of Maternal-Fetal Medicine, Inova Fairfax Medical Campus, Falls Church, 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