AIMC Topic: Cesarean Section
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Cohort profile: Japanese human milk study, a prospective birth cohort: baseline data for lactating women, infants and human milk macronutrients.
BMJ open
Dec 30, 2021
PURPOSE: The Japanese Human Milk Study, a longitudinal prospective cohort study, was set up to clarify how maternal health, nutritional status, lifestyle and sociodemographic and economic factors affect breastfeeding practices and human milk composit...
Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation.
Journal of medical Internet research
Dec 10, 2021
Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across hea...
Machine learning approach to needle insertion site identification for spinal anesthesia in obese patients.
BMC anesthesiology
Oct 18, 2021
BACKGROUND: Ultrasonography for neuraxial anesthesia is increasingly being used to identify spinal structures and the identification of correct point of needle insertion to improve procedural success, in particular in obesity. We developed an ultraso...
Use of an artificial intelligence-based rule extraction approach to predict an emergency cesarean section.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Sep 6, 2021
OBJECTIVE: One of the major problems with artificial intelligence (AI) is that it is generally known as a "black box". Therefore, the present study aimed to construct an emergency cesarean section (CS) prediction system using an AI-based rule extract...
Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.
Scientific reports
Sep 1, 2021
Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bacterial 16S marker gene but have not reported the metabolic function of the gut microbiome, which may ...
Multidisciplinary Approach to Robotic Resection of Abdominal Wall Endometriosis and Mesh Repair.
Journal of minimally invasive gynecology
May 21, 2021
STUDY OBJECTIVE: To demonstrate a technique for robot-assisted laparoscopic excision of abdominal wall endometriosis and mesh reinforcement of the subsequent defect.
A prediction model using machine-learning algorithm for assessing intrathecal hyperbaric bupivacaine dose during cesarean section.
BMC anesthesiology
Apr 14, 2021
BACKGROUND: The intrathecal hyperbaric bupivacaine dosage for cesarean section is difficult to predetermine. This study aimed to develop a decision-support model using a machine-learning algorithm for assessing intrathecal hyperbaric bupivacaine dose...
Three machine learning algorithms and their utility in exploring risk factors associated with primary cesarean section in low-risk women: A methods paper.
Research in nursing & health
Mar 2, 2021
Machine learning, a branch of artificial intelligence, is increasingly used in health research, including nursing and maternal outcomes research. Machine learning algorithms are complex and involve statistics and terminology that are not common in he...
Robotic CSP Resection and Hysterotomy Repair.
Journal of minimally invasive gynecology
Nov 27, 2020
STUDY OBJECTIVE: To demonstrate a technique for the robot-assisted laparoscopic surgical management of cesarean section scar ectopic pregnancy (CSP) and hysterotomy repair.
Classifying the type of delivery from cardiotocographic signals: A machine learning approach.
Computer methods and programs in biomedicine
Aug 18, 2020
BACKGROUND AND OBJECTIVE: Cardiotocography (CTG) is the most employed methodology to monitor the foetus in the prenatal phase. Since the evaluation of CTG is often visual, and hence qualitative and too subjective, some automated methods have been int...
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