Community detection algorithms in healthcare applications: a systematic review
Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
Semi-supervised and un-supervised clustering: A review and experimental evaluation
K Taha - Information Systems, 2023 - Elsevier
Retrieving, analyzing, and processing large data can be challenging. An effective and
efficient mechanism for overcoming these challenges is to cluster the data into a compact …
efficient mechanism for overcoming these challenges is to cluster the data into a compact …
Dynamic line rating forecasting algorithm for a secure power system network
This research aimed to enhance the capacity of transmission lines by develo** an
algorithm to predict Dynamic Line Rating (DLR) to avert the curtailment of renewable energy …
algorithm to predict Dynamic Line Rating (DLR) to avert the curtailment of renewable energy …
Heart disease classification using data mining tools and machine learning techniques
Nowadays, in healthcare industry, data analysis can save lives by improving the medical
diagnosis. And with the huge development in software engineering, different data mining …
diagnosis. And with the huge development in software engineering, different data mining …
AI-powered blockchain technology for public health: A contemporary review, open challenges, and future research directions
Blockchain technology has been growing at a substantial growth rate over the last decade.
Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application …
Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application …
[HTML][HTML] Machine learning-enabled estimation of crosswind load effect on tall buildings
This paper presents an approach to predict crosswind force spectra and associated
response of tall buildings with rectangular cross-section based on machine learning (ML) …
response of tall buildings with rectangular cross-section based on machine learning (ML) …
EGD-SNet: A computational search engine for predicting an end-to-end machine learning pipeline for Energy Generation & Demand Forecasting
Load forecasting avoids energy wastage by accurately estimating the future quantity of
energy generation and demand. Existing load forecasting approaches do not utilize the …
energy generation and demand. Existing load forecasting approaches do not utilize the …
RETRACTED: Evolution from ancient medication to human‐centered Healthcare 4.0: A review on health care recommender systems
D Sharma, G Singh Aujla, R Bajaj - International Journal of …, 2023 - Wiley Online Library
The evolution of intelligent and data‐driven systems has pushed for the tectonic transition
from ancient medication to human‐centric Healthcare 4.0. The rise of Internet of Things …
from ancient medication to human‐centric Healthcare 4.0. The rise of Internet of Things …
Pressure pattern recognition in buildings using an unsupervised machine-learning algorithm
Owing to its significance in ensuring structural safety and occupant comfort, wind pressure
on buildings has attracted the attention of numerous scholars. However, the characteristics …
on buildings has attracted the attention of numerous scholars. However, the characteristics …
Object-based change detection for vegetation disturbance and recovery using Landsat time series
Z Wang, C Wei, X Liu, L Zhu, Q Yang… - GIScience & Remote …, 2022 - Taylor & Francis
Accurate characterization of historical trends in vegetation change at the landscape scale is
necessary for resource management and ecological assessment. Vegetation disturbance …
necessary for resource management and ecological assessment. Vegetation disturbance …