An Hybrid Approach for Prediction Based Health Monitoring in Pregnant Women

Lakshmi, Baddireddi Subhadra; Indumathi, T. S.; Ravi, Nandini

doi:10.1016/j.protcy.2016.05.171

Cited by 17 publications

(12 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Lakshmi.B.N, et al [4] Pregnancy is a delicate stage in women life monitoring during pregnancy period can control, manage maintain and prevent abnormalities induced in physiological parameters, In paper performance of the final rule-set generated from C4.5 provides great, precise, reliable and accurate prediction and an accuracy percentage of 98%. Hence, hybrid approach involving data transformation, C4.5 classifier application, rule extraction and range replacement gives better performance, accurate risk prediction, valid set of rules for further implementation and reliable solution to the complications faced by pregnant women during pregnancy.…”

Section: Related Workmentioning

confidence: 99%

“…If blood sugar levels are too high, it can cause the baby to put on extra weight, particularly in the upper body called macrosomia. Delivery can sometimes result in a fractured bone or nerve damage, the baby may suffer brain damage from lack of oxygen during this process, need to deliver a broad-shouldered baby can lead to injuries to the vaginal area or require a large episiotomy for the mother and risk of new born jaundice is increased [4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Women Health Monitoring: A Survey

Shegokar¹,

Paswan²

2017

International Journal of Advanced Research in Computer and Comm

View full text Add to dashboard Cite

Abstract:In medical area, various problem exist but gestation stage serious problem regarding women. Women undergo several physiological parameter changes which cause major problem. When we neglect such problem may result in complications or mortality of mother and fetus, so we need to protect pregnant women. In this paper we have discussed a few approaches for find risk during pregnancy and information regarding health care.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Women Health Monitoring: A Survey

Shegokar¹,

Paswan²

2017

International Journal of Advanced Research in Computer and Comm

View full text Add to dashboard Cite

show abstract

“…However, the process is far from satisfactory. Most recent advances in pregnancy outcome prediction use data collected after mothers get pregnant [3][4][5]. In this situation, if an adverse pregnancy outcome is diagnosed, the parents will suffer physically, financially and emotionally.…”

Section: Introductionmentioning

confidence: 99%

Applying deep learning for adverse pregnancy outcome detection with pre-pregnancy health data

Feng

Yang

et al. 2018

MATEC Web Conf.

View full text Add to dashboard Cite

Abstract. Adverse pregnancy outcomes can bring enormous losses to both families and the society. Thus, pregnancy outcome prediction stays a crucial research topic as it may help reducing birth defect and improving the quality of population. However, recent advances in adverse pregnancy outcome detection are driven by data collected after mothers having been pregnant. In this situation, if a bad pregnancy outcome is diagnosed, the parents will suffer both physically and emotionally. In this paper, we develop a deep learning algorithm which is able to detect and classify adverse pregnancy outcomes before parents getting pregnant. We train a multi-layer neural network by using a dataset of 75542 couples' multidimension pre-pregnancy health data. Our model outperforms some of algorithms in accuracy, recall and F1 score.

show abstract

“…Haemorrhage, infection, hypertension, and obstructed labor contribute to maternal illness and also causes fatality if the proper screening is not undertaken. Diseases like malaria, HIV infection, pneumonia, tuberculosis, and herpes virus infection can complicate health of the mother [7] [8]. The check-ups during pregnancy, before birth, is known as antenatal care.…”

Section: Introductionmentioning

confidence: 99%

Contextual Care Protocol using Neural Networks and Decision Trees

Sinha

Malviya

Panda

et al. 2018

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)

View full text Add to dashboard Cite

A contextual care protocol is used by a medical practitioner for patient healthcare, given the context or situation that the specified patient is in. This paper proposes a method to build an automated self-adapting protocol which can help make relevant, early decisions for effective healthcare delivery. The hybrid model leverages neural networks and decision trees. The neural network estimates the chances of each disease and each tree in the decision trees represents care protocol for a disease. These trees are subject to change in case of aberrations found by the diagnosticians. These corrections or prediction errors are clustered into similar groups for scalability and review by the experts. The corrections as suggested by the experts are incorporated into the model.

show abstract

An Hybrid Approach for Prediction Based Health Monitoring in Pregnant Women

Cited by 17 publications

References 0 publications

Women Health Monitoring: A Survey

Women Health Monitoring: A Survey

Applying deep learning for adverse pregnancy outcome detection with pre-pregnancy health data

Contextual Care Protocol using Neural Networks and Decision Trees

Contact Info

Product

Resources

About