استخراج نظام‌مند آیتم‌های داده‌ای لازم برای تشخیص بارداری‌های شایع پرخطر با استفاده از رویکرد دلفی

دلدار, کلثوم, تارا, میرزائیان, پورحسینی… - مجله زنان، مامایی و …, 2017‎ - ijogi.mums.ac.ir
مقدمه: در زمان مشاوره تلفنی رزیدنت-استاد، کیفیت تصمیمات بالینی پزشک آنکال وابستگی
شدیدی به کیفیت اطلاعات دریافتی از رزیدنت دارد. برخی فاکتورها از جمله نوع، تعداد، قالب …

[PDF][PDF] Identifying high risk pregnancy and its effectiveness in determining maternal and perinatal outcome

J Shrestha, SD Gurung, A Subedi… - Birat Journal of …, 2021 - pdfs.semanticscholar.org
ORA - 271 - Dr Junu Shrestha.cdr Page 1 Original Research Ar cle Shrestha J et al 1. Associate
Professor, Department of Obstetrics and Gynaecology, Manipal College of Medical Sciences …

[PDF][PDF] DEVELOPMENT OF A PREDICTIVE MODEL FOR THE RISK OF INFERTILITY IN WOMEN USING SUPERVISED MACHINE LEARNING ALGORITHMS

JA Balogun, PA Idowu, OT Babawale - researchgate.net
Infertility is a worldwide problem, affecting 8%–15% of couples in their reproductive age.
Infertility has caused considerable social, emotional and psychological stress between …

Systematic extraction of diagnostic data items for common high-risk pregnancies using Delphi technique

K Deldar, SM Tara, M Jangi - Medical Technologies Journal, 2017 - medtech.ichsmt.org
Methods A multi-stage cross-sectional study was conducted to exploit the diagnostic items
for the most common high-risk pregnancies in three obstetrics and gynecology department …

[PDF][PDF] Rule-based inferencing system for infertility diagnosis in women

K Robindro, K Nilakanta - Int J Artif Intell Appl, 2017 - academia.edu
Childlessness among married couples is a rising problem in India. One of the major factors
of childlessness is due to being infertile of either one or both of wife or husband. Infertility …

Early assessment of pregnancy using machine learning

C Prabha, M Gupta - Artificial Intelligence and Machine Learning for …, 2024 - Elsevier
Artificial intelligence has become prevalent in the field of medicine, and machine learning
(ML) is finding increasing applications in medical treatment, estimation, and assessment, as …

[HTML][HTML] Reliable prediction models based on enriched data for identifying the mode of childbirth by using machine learning methods: development study

Z Ullah, F Saleem, M Jamjoom, B Fakieh - Journal of Medical Internet …, 2021 - jmir.org
Background The use of artificial intelligence has revolutionized every area of life such as
business and trade, social and electronic media, education and learning, manufacturing …

Detecting Pregnancy Risk Type Using LSTM Algorithm

GM Damaraji, AE Permanasari… - 2022 4th …, 2022 - ieeexplore.ieee.org
Pregnancy is the most important yet vulnerable phase for all mothers-to-be. Approximately
nine months of pregnancy requires special attention from medical workers to monitor the …

High risk scoring for prediction of pregnancy outcome: a prospective study

S Jain, S Anand, R Aherwar - International Journal of Reproduction …, 2014 - go.gale.com
Background: Objectives of current study were to detect high risk factors in pregnancy and to
develop a simple scoring system to identify and categorize high risk pregnancies and to …

Predicting Premature Birth During Pregnancy Using Machine Learning: A Systematic Review

A Sari, MM Lakulu, IY Panessai - … of Intelligent Systems and Applications in …, 2024 - ijisae.org
Artificial intelligence is widely developed in the health sector, and machine learning has
been increasingly used in healthcare to make predictions, assign diagnoses and as a …