Introduction to Machine Learning in Obstetrics and Gynecology. Issue 4 (10th April 2022)
- Record Type:
- Journal Article
- Title:
- Introduction to Machine Learning in Obstetrics and Gynecology. Issue 4 (10th April 2022)
- Main Title:
- Introduction to Machine Learning in Obstetrics and Gynecology
- Authors:
- Shazly, Sherif A.
Trabuco, Emanuel C.
Ngufor, Che G.
Famuyide, Abimbola O. - Abstract:
- Abstract : This article reviews the history and applications of artificial intelligence and its capacity to support clinical research and practice in the field of obstetrics and gynecology. Abstract : In the digital age of the 21st century, we have witnessed an explosion in data matched by remarkable progress in the field of computer science and engineering, with the development of powerful and portable artificial intelligence–powered technologies. At the same time, global connectivity powered by mobile technology has led to an increasing number of connected users and connected devices. In just the past 5 years, the convergence of these technologies in obstetrics and gynecology has resulted in the development of innovative artificial intelligence–powered digital health devices that allow easy and accurate patient risk stratification for an array of conditions spanning early pregnancy, labor and delivery, and care of the newborn. Yet, breakthroughs in artificial intelligence and other new and emerging technologies currently have a slow adoption rate in medicine, despite the availability of large data sets that include individual electronic health records spanning years of care, genomics, and the microbiome. As a result, patient interactions with health care remain burdened by antiquated processes that are inefficient and inconvenient. A few health care institutions have recognized these gaps and, with an influx of venture capital investments, are now making in-roads inAbstract : This article reviews the history and applications of artificial intelligence and its capacity to support clinical research and practice in the field of obstetrics and gynecology. Abstract : In the digital age of the 21st century, we have witnessed an explosion in data matched by remarkable progress in the field of computer science and engineering, with the development of powerful and portable artificial intelligence–powered technologies. At the same time, global connectivity powered by mobile technology has led to an increasing number of connected users and connected devices. In just the past 5 years, the convergence of these technologies in obstetrics and gynecology has resulted in the development of innovative artificial intelligence–powered digital health devices that allow easy and accurate patient risk stratification for an array of conditions spanning early pregnancy, labor and delivery, and care of the newborn. Yet, breakthroughs in artificial intelligence and other new and emerging technologies currently have a slow adoption rate in medicine, despite the availability of large data sets that include individual electronic health records spanning years of care, genomics, and the microbiome. As a result, patient interactions with health care remain burdened by antiquated processes that are inefficient and inconvenient. A few health care institutions have recognized these gaps and, with an influx of venture capital investments, are now making in-roads in medical practice with digital products driven by artificial intelligence algorithms. In this article, we trace the history, applications, and ethical challenges of the artificial intelligence that will be at the forefront of digitally transforming obstetrics and gynecology and medical practice in general. … (more)
- Is Part Of:
- Obstetrics and gynecology. Volume 139:Issue 4(2022)
- Journal:
- Obstetrics and gynecology
- Issue:
- Volume 139:Issue 4(2022)
- Issue Display:
- Volume 139, Issue 4 (2022)
- Year:
- 2022
- Volume:
- 139
- Issue:
- 4
- Issue Sort Value:
- 2022-0139-0004-0000
- Page Start:
- 669
- Page End:
- 679
- Publication Date:
- 2022-04-10
- Subjects:
- Obstetrics -- Periodicals
Gynecology -- Periodicals
618 - Journal URLs:
- http://journals.lww.com/greenjournal/pages/default.aspx ↗
http://journals.lww.com ↗ - DOI:
- 10.1097/AOG.0000000000004706 ↗
- Languages:
- English
- ISSNs:
- 0029-7844
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6208.200000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21551.xml