Computer applications in obstetrics

Catanzarite, Val; Jelovsek, Frederick R.

doi:10.1016/0002-9378(87)90109-8

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…Table 1 presents studies by pregnancy stage, with an overview of the methodology and results. Not included in Table 1 is one evaluation of an application described in an included paper [ 18 ], and 8 review papers, reviewing applications in the following: general obstetrics [ 19 ], translational science [ 20 ], intrapartum surveillance [ 21 , 22 ], fetal heart rate (FHR) [ 23 ], labor fetal assessment [ 24 ], ART [ 12 ] and mobile health (mHealth) for antepartum care [ 25 ]. AI may help address challenges in birth defects research.…”

Section: Resultsmentioning

confidence: 99%

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Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes

Davidson

Boland

2021

Briefings in Bioinformatics

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Objective Development of novel informatics methods focused on improving pregnancy outcomes remains an active area of research. The purpose of this study is to systematically review the ways that artificial intelligence (AI) and machine learning (ML), including deep learning (DL), methodologies can inform patient care during pregnancy and improve outcomes. Materials and methods We searched English articles on EMBASE, PubMed and SCOPUS. Search terms included ML, AI, pregnancy and informatics. We included research articles and book chapters, excluding conference papers, editorials and notes. Results We identified 127 distinct studies from our queries that were relevant to our topic and included in the review. We found that supervised learning methods were more popular (n = 69) than unsupervised methods (n = 9). Popular methods included support vector machines (n = 30), artificial neural networks (n = 22), regression analysis (n = 17) and random forests (n = 16). Methods such as DL are beginning to gain traction (n = 13). Common areas within the pregnancy domain where AI and ML methods were used the most include prenatal care (e.g. fetal anomalies, placental functioning) (n = 73); perinatal care, birth and delivery (n = 20); and preterm birth (n = 13). Efforts to translate AI into clinical care include clinical decision support systems (n = 24) and mobile health applications (n = 9). Conclusions Overall, we found that ML and AI methods are being employed to optimize pregnancy outcomes, including modern DL methods (n = 13). Future research should focus on less-studied pregnancy domain areas, including postnatal and postpartum care (n = 2). Also, more work on clinical adoption of AI methods and the ethical implications of such adoption is needed.

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Section: Resultsmentioning

confidence: 99%

“…Reviews found great promise in AI applications, but not realized in clinical care [ 21 , 22 , 25 ], or missing external validation [ 12 ]. AI applications are warned as adjunct, not replacement, of healthcare professionals [ 19 , 23 ]. One review found no evidence supporting improved pregnancy outcomes with AI applications [ 24 ].…”

Section: Resultsmentioning

confidence: 99%

Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes

Davidson

Boland

2021

Briefings in Bioinformatics

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“…Recently, CAl has proliferated in almost every clinical discipline of medicine [22][23][24] as a result of both the GPEP report [1] and the simultaneous proliferation of microcomputers. CAl offers the advantages of interactive learning, immediate, specific feedback, individually tailored instruction, objective testing, and an entertaining presentation [21].…”

Section: Discussionmentioning

confidence: 99%

Computer-Assisted Instruction in Probabilistic Reasoning During the Inpatient Medicine Clerkship

Smith¹,

Lancaster²,

McClish³

1993

Methods Inf Med

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The acceptability and utility of computer-assisted instruction in probabilistic reasoning was assessed for medicine clerkship students. After a pretest, the experimental (n = 40), but not the control students (n = 39), completed a program that we designed. The program contained the test and its answers. After program exposure, experimental students rated their knowledge of the program’s content significantly higher (p = 10−4) than control students. On the identical posttest, experimental students also scored significantly higher than control students (p = 10−4) and improved their scores significantly more (p = 10−3). They rated ease-of-use items significantly higher than content-relevance items (p = 1CT−4). We conclude that computer-assisted instruction in probabilistic reasoning is acceptable to clerkship students, and that it may improve their knowledge and skills in this area. However, students may rate the vehicle of this instruction more highly than its content.

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“…La programación y desarrollo experimental de software obstétrico sustentado y escalonado en modelos simples, evoluciona hasta las potentes herramientas actuales, de la mano con la vertiginosa evolución tecnológica que se traduce en hardware más potentes asociados a una reducción sustancial de los costos (13,14). Específicamente, el uso informático en la obstetricia se ha enfocado hacia diversas áreas (13,15) (Tabla I).…”

Section: Introductionunclassified

“…Específicamente, el uso informático en la obstetricia se ha enfocado hacia diversas áreas (13,15) (Tabla I).…”

Section: Introductionunclassified

Conceptos en Torno a La Informática en Obstetricia

A¹,

F³

2007

Rev. chil. obstet. ginecol.

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RESUMENLa obstetricia contemporánea debe apoyarse en el uso adecuado de la información a fin de evaluar la eficacia y calidad de sus intervenciones permanentemente. Los avances vertiginosos experimentados en el último cuarto de siglo, sumado a la consolidación del concepto de medicina materno-fetal, han obligado a los clínicos a trabajar con múltiples variables biológicas en función de mantener una visión permanente de las condiciones que afectan al binomio madre-hijo. Esta vigilancia lineal multivariable hace imprescindible el uso estratégico de herramientas informáticas con ventajas claras sobre el ordenamiento, comparación y análisis de información, para una consecuente planificación y ejecución de acciones efectivas, disminuyendo costos y optimizando recursos. El presente artículo describe la conceptualización, evolución y situación actual de la informática en el área de la Medicina Materno-Fetal. Además, agrega conceptos y recomendaciones básicas sobre el manejo de la información digital. PALABRAS CLAVE: Computador, informática, base de datos SUMMARYContemporary obstetrics must rely on the suitable use of information to permanently assess the effectiveness and quality of its interventions. The vertiginous advances in the last quarter of the century, and the consolidation of the feto-maternal specialization, have forced the physicians to work with multiple biological variables based on maintaining a permanent vision of the fetal-maternal relationship through time. The necessity of using a multi-variate linear analysis makes the strategic of incorporating software tools a big advantage for researches and clinicians. Furthermore, there are clear advantages over the arrangement, comparison and analysis of information, in order to achieve an adequate planning and execution of effective actions, thus reducing the costs and optimizing resources. The aim of this study is to describe the evolution and current concepts and state of the art in computer science applying to feto-maternal area. In addition, this review take into account the basic concepts and recommendations on the handling of digital information.

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Computer applications in obstetrics

Cited by 8 publications

References 8 publications

Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes

Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes

Computer-Assisted Instruction in Probabilistic Reasoning During the Inpatient Medicine Clerkship

Conceptos en Torno a La Informática en Obstetricia

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