Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction

A Raza, HUR Siddiqui, K Munir, M Almutairi, F Rustam… - Plos one, 2022 - journals.plos.org
Maternal health is an important aspect of women's health during pregnancy, childbirth, and
the postpartum period. Specifically, during pregnancy, different health factors like age, blood …

A review on predicting autism spectrum disorder (asd) meltdown using machine learning algorithms

S Karim, N Akter, MJA Patwary… - 2021 5th International …, 2021 - ieeexplore.ieee.org
Autism Spectrum Disorder (ASD) is a well-known mental disorders that prevails in the ability
of a person's social communication. The significance of early diagnosing drew the attention …

Examining mental disorder/psychological chaos through various ML and DL techniques: a critical review

AB Osman, F Tabassum, MJA Patwary… - Annals of Emerging …, 2022 - papers.ssrn.com
Mental soundness is a condition of well-being wherein a person understands his/her
potential, participates in his or her community and is able to deal effectively with the …

Fuzziness based semi-supervised multimodal learning for patient's activity recognition using RGBDT videos

MJA Patwary, W Cao, XZ Wang, MA Haque - Applied Soft Computing, 2022 - Elsevier
Automatic recognition of bedridden patients' physical activity has important applications in
the clinical process. Such recognition tasks are usually accomplished on visual data …

Bank deposit prediction using ensemble learning

MJA Patwary, S Akter, MSB Alam… - Artificial Intelligence …, 2021 - ojs.wiserpub.com
Bank deposit is one of the vital issues for any financial institution. It is very challenging to
predict a customer if he/she can be a depositor by analyzing related information. Some …

Ensemble based machine learning model for early detection of mother's delivery mode

M Hasan, MJ Zobair, S Akter, M Ashef… - 2023 International …, 2023 - ieeexplore.ieee.org
The mother's mode of delivery greatly impacts the relationship between the newborn baby
and the mother, as well as the mother's and baby's health. Currently, the cesarean rate is …

Predicting autism spectrum disorder (ASD) meltdown using fuzzy semi-supervised learning with NNRW

S Karim, N Akter, MJA Patwary - 2022 International Conference …, 2022 - ieeexplore.ieee.org
Autism Spectrum Condition (ASD) is a notable psychological disorder that affects a human's
ability to communicate socially. The need of early diagnosis prompted researchers' attention …

Impact of fuzziness for skin lesion classification with transformer-based model

I Yasmin, S Sultana, SJ Begum… - 2023 International …, 2023 - ieeexplore.ieee.org
Skin lesion is one of the most commonly encountered illnesses that need to be detected and
treated at an early stage. Numerous Convolutional Neural Network (CNN) classifiers were …

The impact of data balancing on the classifier's performance in predicting cesarean childbirth

M Hasan, MM Islam, SW Sajid… - 2022 4th International …, 2022 - ieeexplore.ieee.org
The number of cesarean sections delivered world-wide is increasing at an alarming rate. It
has a negative influence on the health of both mother and child, as well as on the economy …

An Optimized Bagging Ensemble Learning Approach Using BESTrees for Predicting Students' Performance

E Evangelista - … Journal of Emerging Technologies in Learning …, 2023 - zuscholars.zu.ac.ae
Every academic institution's goal is to identify students who require additional assistance
and take appropriate actions to improve their performance. As such, various research …