A Review of Machine Learning's Role in Cardiovascular Disease Prediction: Recent Advances and Future Challenges
Cardiovascular disease is the leading cause of global mortality and responsible for millions
of deaths annually. The mortality rate and overall consequences of cardiac disease can be …
of deaths annually. The mortality rate and overall consequences of cardiac disease can be …
Optimizing machine learning algorithms for landslide susceptibility map** along the Karakoram Highway, Gilgit Baltistan, Pakistan: A comparative study of baseline …
Algorithms for machine learning have found extensive use in numerous fields and
applications. One important aspect of effectively utilizing these algorithms is tuning the …
applications. One important aspect of effectively utilizing these algorithms is tuning the …
Recent advancements and future prospects in active deep learning for medical image segmentation and classification
Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …
medical image segmentation improves diagnosis and decision-making, aiding intelligent …
Particle swarm optimization of Elman neural network applied to battery state of charge and state of health estimation
Lithium-ion batteries have emerged as an energy storage solution for electrified vehicles. A
Battery Management System (BMS) is critical for efficient and reliable system operation, in …
Battery Management System (BMS) is critical for efficient and reliable system operation, in …
Enhancing time series forecasting with an optimized binary gravitational search algorithm for echo state networks
The echo state network (ESN) is a cutting-edge reservoir computing technique designed to
handle time-dependent data, making it highly effective for addressing time series prediction …
handle time-dependent data, making it highly effective for addressing time series prediction …
Classical, evolutionary, and deep learning approaches of automated heart disease prediction: a case study
Cardiovascular diseases (CVDs) are the leading cause of death globally. Detecting this kind
of disease represents the principal concern of many scientists, and techniques belonging to …
of disease represents the principal concern of many scientists, and techniques belonging to …
Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models
K Khandelwal, AK Dalai - Molecules, 2024 - mdpi.com
Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway
for the production of hydrogen. However, SCWG is a complex thermochemical process, the …
for the production of hydrogen. However, SCWG is a complex thermochemical process, the …
[HTML][HTML] A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture
G Zhang, J Liu, W Luo, Y Zhao, R Tang, K Mei, P Wang - Sensors, 2024 - mdpi.com
Unmanned aerial vehicles (UAVs) have made significant advances in autonomous sensing,
particularly in the field of precision agriculture. Effective path planning is critical for …
particularly in the field of precision agriculture. Effective path planning is critical for …
Robust Deep Neural Network-Based Framework for Predicting and Classifying Capsid Protein Based on Biomedical Data
Capsid protein is a pathogenic protein that needs to be examined because it helps in the
virus's proliferation and mutation. Due to this protein, the virus can replicate and reproduce …
virus's proliferation and mutation. Due to this protein, the virus can replicate and reproduce …
Hybrid whale algorithm with evolutionary strategies and filtering for high-dimensional optimization: Application to microarray cancer data
The standard whale algorithm is prone to suboptimal results and inefficiencies in high-
dimensional search spaces. Therefore, examining the whale optimization algorithm …
dimensional search spaces. Therefore, examining the whale optimization algorithm …