Artificial intelligence in pregnancy: A sco** review

AM Oprescu, G Miro-Amarante, L García-Díaz… - IEEE …, 2020 - ieeexplore.ieee.org
Artificial Intelligence has been widely applied to a majority of research areas, including
health and medicine. Certain complications or disorders that can appear during pregnancy …

[PDF][PDF] Network Forensics: A Comprehensive Review of Tools and Techniques

S Qureshi, S Tunio, F Akhtar… - International …, 2021 - pdfs.semanticscholar.org
With the evolution and popularity of computer networks, a tremendous amount of devices
are increasingly being added to the global internet connectivity. Additionally, more …

Infant birth weight estimation and low birth weight classification in United Arab Emirates using machine learning algorithms

W Khan, N Zaki, MM Masud, A Ahmad, L Ali, N Ali… - Scientific reports, 2022 - nature.com
Accurate prediction of a newborn's birth weight (BW) is a crucial determinant to evaluate the
newborn's health and safety. Infants with low BW (LBW) are at a higher risk of serious short …

Identification of soil texture classes under vegetation cover based on Sentinel-2 data with SVM and SHAP techniques

Y Zhou, W Wu, H Wang, X Zhang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Understanding the spatial variability of soil texture classes is essential for agricultural
management and environment sustainability. Sentinel-2 data offer valuable vegetation …

An empirical evaluation of stacked ensembles with different meta-learners in imbalanced classification

S Zian, SA Kareem, KD Varathan - IEEE Access, 2021 - ieeexplore.ieee.org
The selection of a meta-learner determines the success of a stacked ensemble as the meta-
learner is responsible for the final predictions of the stacked ensemble. Unfortunately, in …

Identifying first-trimester risk factors for SGA-LGA using weighted inheritance voting ensemble learning

SN Van, J Cui, Y Wang, H Jiang, F Sha, Y Li - Bioengineering, 2024 - mdpi.com
The classification of fetuses as Small for Gestational Age (SGA) and Large for Gestational
Age (LGA) is a critical aspect of neonatal health assessment. SGA and LGA, terms used to …

Breast mass detection and classification using deep convolutional neural networks for radiologist diagnosis assistance

T Mahmood, J Li, Y Pei, F Akhtar, Y Jia… - 2021 IEEE 45th …, 2021 - ieeexplore.ieee.org
Several developments in computational image processing methods assist the radiologist in
detecting abnormal breast tissue in recent years. Consequently, deep learning-based …

Building a predictive model of low birth weight in low-and middle-income countries: a prospective cohort study

JK Patterson, VR Thorsten, B Eggleston… - BMC Pregnancy and …, 2023 - Springer
Background Low birth weight (LBW,< 2500 g) infants are at significant risk for death and
disability. Improving outcomes for LBW infants requires access to advanced neonatal care …

Performance of cryptographic algorithms based on time complexity

K Ali, F Akhtar, SA Memon, A Shakeel… - 2020 3rd …, 2020 - ieeexplore.ieee.org
Nowadays, a tremendous amount of data is produced every single day by computational
systems and electronic instruments, whether its an online transaction or data manipulation …

An innovative supervised longitudinal learning procedure of recurrent neural networks with temporal data augmentation: Insights from predicting fetal macrosomia and …

R Liu, Y Yao, C Zhang, B Zhang - Computers in Biology and Medicine, 2024 - Elsevier
Background Longitudinal data in health informatics studies often presented challenges due
to sparse observations from each subject, limiting the application of contemporary deep …