Prediction of preeclampsia using machine learning and deep learning models: a review

SS Aljameel, M Alzahrani, R Almusharraf… - Big Data and Cognitive …, 2023 - mdpi.com
Preeclampsia is one of the illnesses associated with placental dysfunction and pregnancy-
induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by …

LSTM recurrent neural network for hand gesture recognition using EMG signals

A Toro-Ossaba, J Jaramillo-Tigreros, JC Tejada… - Applied Sciences, 2022 - mdpi.com
Currently, research on gesture recognition systems has been on the rise due to the
capabilities these systems provide to the field of human–machine interaction, however …

A hybrid system based on LSTM for short-term power load forecasting

Y Jin, H Guo, J Wang, A Song - Energies, 2020 - mdpi.com
As the basic guarantee for the reliability and economic operations of state grid corporations,
power load prediction plays a vital role in power system management. To achieve the …

Prediction of COVID-19 data using improved ARIMA-LSTM hybrid forecast models

YC Jin, Q Cao, KN Wang, Y Zhou, YP Cao… - IEEE …, 2023 - ieeexplore.ieee.org
COVID-19 has developed into a global public health emergency and has led to restrictions
in numerous nations. Thousands of deaths have resulted from the infection of millions of …

A Theoretical Exploration of Artificial Intelligence's Impact on Feto-Maternal Health from Conception to Delivery

I Yaseen, RA Rather - International Journal of Women's Health, 2024 - Taylor & Francis
Abstract The implementation of Artificial Intelligence (AI) in healthcare is enhancing
diagnostic accuracy in clinical setups. The use of AI in healthcare is steadily increasing with …

[PDF][PDF] Prediction of sea surface current velocity and direction using LSTM

II Zulfa, D Candra, R Novitasari, F Setiawan… - Indones. J. Electron …, 2021 - academia.edu
Labuan Bajo is considered to have an important role as a transportation route for traders
and tourists. Therefore, it is necessary to have a further understanding of the condition of the …

[PDF][PDF] Algoritma Deep Learning-LSTM untuk Memprediksi Umur Transformator

AA Ningrum, I Syarif, AI Gunawan… - … Informasi dan Ilmu …, 2021 - researchgate.net
Kualitas dan ketersediaan pasokan listrik menjadi hal yang sangat penting. Kegagalan
pada transformator menyebabkan pemadaman listrik yang dapat menurunkan kualitas …

Research on Long-Term Tidal-Height-Prediction-Based Decomposition Algorithms and Machine Learning Models

W Ban, L Shen, F Lu, X Liu, Y Pan - Remote Sensing, 2023 - mdpi.com
Tidal-level prediction is crucial for ensuring the safety and efficiency of offshore marine
activities, port and channel management, water transportation resource development, and …

[PDF][PDF] Crude Oil Price Forecasting Using Long Short-Term Memory

MF Maulana, S Sa'adah, PE Yunanto - Jurnal Ilmiah Teknik Elektro …, 2021 - academia.edu
Crude oil has an important role in the financial indicators of global markets and economies.
The price of crude oil influences the income of a country, both directly and indirectly. This …

Performance evaluation of pre-trained convolutional neural network and transfer learning for classification of spices and herbal medicines in Madura

M Tahir, AA Jakfar, DB Elnursa… - … of Computer Science …, 2023 - ieeexplore.ieee.org
Spices are one of Indonesia's wealth. Based on the data owned. The Negara Rempah
Foundation has around 400 to 500 species of herbs worldwide, and 275 types of spices are …