Machine Learning-Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic Review and Future Directions

Javeed, Ashir; Khan, Shafqat Ullah; Ali, Liaqat; Ali, Sarfraz; Imrana, Yakubu; Rahman, Atiqur

doi:10.1155/2022/9288452

Cited by 58 publications

(35 citation statements)

References 145 publications

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“…PPH is a common complication after cesarean section, and uterine weakness is one of the main causes of PPH [ 9 ]. PPH is urgent and develops rapidly, requiring active and effective treatment; otherwise it may cause functional ischemia of multiple organs, hypovolemic shock, etc., and seriously affect the maternal quality of life [ 10 ].…”

Section: Discussionmentioning

confidence: 99%

Effect of Uterine Artery Ligation and Uterine Artery Embolization on Postpartum Hemorrhage Due to Uterine Asthenia after Cesarean Section and Its Effect on Blood Flow and Function of Uterine and Ovarian Arteries

Liu

Yin

2022

Journal of Healthcare Engineering

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Objective. To investigate the efficacy of uterine artery ligation (UAL) and uterine artery embolization (UAE) in the treatment of uterine asthenia postpartum hemorrhage (PPH) after cesarean section and its effect on uterine and ovarian artery blood flow and function. Methods. 100 patients with uterine asthenia PPH after cesarean section in our hospital from January 2018 to November 2020 were randomly divided into 50 cases in the UAL group and 50 cases in the UAE group. They were followed up for 12 months. The bleeding volume, operation time, immediate hemostasis rate, and hemostasis effective rate; lochia clearance time and menstrual rehydration time; RI and S/D; and serum FSH, E2, and LH levels were compared between the two groups. Results. Compared with the UAL group, the amount of bleeding in the UAE group was significantly increased and the operation time was significantly shortened ( p < 0.05 ). There was no significant difference in the immediate hemostatic rate and hemostatic effective rate between the two groups ( p > 0.05 ). There was no significant difference in lochia clearance time and menstrual rehydration time between the two groups ( p > 0.05 ). There was no significant difference in RI and S/D between the two groups ( p > 0.05 ). Compared with before the operation, the levels of FSH and LH in the two groups decreased significantly, and the level of E2 increased significantly ( p < 0.05 ). There was no significant difference between the two groups ( p > 0.05 ). Conclusion. The efficacy of UAL and UAE in the treatment of PPH with uterine asthenia after cesarean section and its effect on the blood flow and function of uterine and ovarian arteries are equivalent, but the amount of bleeding in UAL is less and the operation time of UAE is shorter. The appropriate operation method can be selected according to the actual situation.

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Section: Discussionmentioning

confidence: 99%

Effect of Uterine Artery Ligation and Uterine Artery Embolization on Postpartum Hemorrhage Due to Uterine Asthenia after Cesarean Section and Its Effect on Blood Flow and Function of Uterine and Ovarian Arteries

Liu

Yin

2022

Journal of Healthcare Engineering

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“…When it comes to data mining, privacy, security, and abuse of information are all major concerns [21]. In [28], several ML techniques for developing automated heart disease detection solutions were examined, unlike earlier studies, which only focused on one methodology. If they're interested in automating the identification of heart disease, they hope this study will be useful.…”

Section: Iirelated Workmentioning

confidence: 99%

An Automated Heart Disease Diagnosis System Using Adaptive Cross-Layer Stacked Residual Convolutional Neural Networks

Kumar

Singh

2022

Preprint

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Heart disease is the devastating illness that kills the most people worldwide when compared to other ailments. Heart disease is a significant hazard. A cardiac problem occurs when the arteries supplying oxygen and blood to the heart become fully clogged or constricted. One of the primary causes of death has been heart disease. In a short period, the mortality rate has grown considerably. Because an incorrect diagnosis of the condition might result in death, accuracy and safe diagnosis of cardiac disease should be a top priority in healthcare. Cardiovascular disease may be avoided if the prognosis is right, but it can potentially be fatal if the prediction is incorrect. Hence, in this paper, we propose an automated heart disease diagnosis system. Initially, the patient data is collected and preprocessed. The features are extracted using Kernel-based Linear Discriminant Analysis (K-LDA). (Correlation-based feature selection) CFS is performed to extract relevant features. We propose Adaptive Cross-Layer Stacked Residual Convolutional Neural Networks (ACLS-RCNN) for the prediction of the disease. We also introduce the Improved Cuttlefish-Swarm Optimization Algorithm (ICSOA) for enhancing the prediction process. The performance metrics like accuracy, precision, recall, and f1-score of the proposed system are evaluated using the python simulation tool and compared with conventional methodologies. Our framework can make a very accurate prediction based on clinical data and diagnoses from the real world.

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“…A large number of algorithms and models have been presented for the diagnosis of cardiac disease. [ 27 ] Potes et al [ 28 ] identified heart sounds with an integrated algorithm and a deep learning algorithm, reaching 86% classification accuracy on the 2016 PhysioNet/CinC Challenge database. Since then, an increasing number of researchers have focused on the identification of cardiac disease using heart sounds.…”

Section: Related Workmentioning

confidence: 99%

A Study on the Association between Korotkoff Sound Signaling and Chronic Heart Failure (CHF) Based on Computer-Assisted Diagnoses

Zhang

Wang

Zhou

et al. 2022

Journal of Healthcare Engineering

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Background. Korotkoff sound (KS) is an important indicator of hypertension when monitoring blood pressure. However, its utility in noninvasive diagnosis of Chronic heart failure (CHF) has rarely been studied. Purpose. In this study, we proposed a method for signal denoising, segmentation, and feature extraction for KS, and a Bayesian optimization-based support vector machine algorithm for KS classification. Methods. The acquired KS signal was resampled and denoised to extract 19 energy features, 12 statistical features, 2 entropy features, and 13 Mel Frequency Cepstrum Coefficient (MFCCs) features. A controlled trial based on the VALSAVA maneuver was carried out to investigate the relationship between cardiac function and KS. To classify these feature sets, the K-Nearest Neighbors (KNN), decision tree (DT), Naive Bayes (NB), ensemble (EM) classifiers, and the proposed BO-SVM were employed and evaluated using the accuracy (Acc), sensitivity (Se), specificity (Sp), Precision (Ps), and F1 score (F1). Results. The ALSAVA maneuver indicated that the KS signal could play an important role in the diagnosis of CHF. Through comparative experiments, it was shown that the best performance of the classifier was obtained by BO-SVM, with Acc (85.0%), Se (85.3%), and Sp (84.6%). Conclusions. In this study, a method for noise reduction, segmentation, and classification of KS was established. In the measured data set, our method performed well in terms of classification accuracy, sensitivity, and specificity. In light of this, we believed that the methods described in this paper can be applied to the early, noninvasive detection of heart disease as well as a supplementary monitoring technique for the prognosis of patients with CHF.

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Machine Learning-Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic Review and Future Directions

Cited by 58 publications

References 145 publications

Effect of Uterine Artery Ligation and Uterine Artery Embolization on Postpartum Hemorrhage Due to Uterine Asthenia after Cesarean Section and Its Effect on Blood Flow and Function of Uterine and Ovarian Arteries

Effect of Uterine Artery Ligation and Uterine Artery Embolization on Postpartum Hemorrhage Due to Uterine Asthenia after Cesarean Section and Its Effect on Blood Flow and Function of Uterine and Ovarian Arteries

An Automated Heart Disease Diagnosis System Using Adaptive Cross-Layer Stacked Residual Convolutional Neural Networks

A Study on the Association between Korotkoff Sound Signaling and Chronic Heart Failure (CHF) Based on Computer-Assisted Diagnoses

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