Predictive analysis of heart diseases with machine learning approaches
TR Ramesh, UK Lilhore, M Poongodi… - Malaysian Journal of …, 2022 - jpmm.um.edu.my
Abstract Machine Learning (ML) is used in healthcare sectors worldwide. ML methods help
in the protection of heart diseases, locomotor disorders in the medical data set. The …
in the protection of heart diseases, locomotor disorders in the medical data set. The …
[HTML][HTML] A hybrid intrusion detection model using ega-pso and improved random forest method
AK Balyan, S Ahuja, UK Lilhore, SK Sharma… - Sensors, 2022 - mdpi.com
Due to the rapid growth in IT technology, digital data have increased availability, creating
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
Hybrid model for detection of cervical cancer using causal analysis and machine learning techniques
UK Lilhore, M Poongodi, A Kaur… - … Methods in Medicine, 2022 - Wiley Online Library
Cervical cancer has become the third most common form of cancer in the in‐universe, after
the widespread breast cancer. Human papillomavirus risk of infection is linked to the …
the widespread breast cancer. Human papillomavirus risk of infection is linked to the …
(Benefits of Internet of Things (IoT) Applications in Health care-An Overview)
In a nutshell, the IoT refers to the idea of integrating high-tech technology in the form of"
smart" gadgets and sensors into a single setting to gather data. There are still numerous …
smart" gadgets and sensors into a single setting to gather data. There are still numerous …
[HTML][HTML] Next-generation cyber attack prediction for IoT systems: leveraging multi-class SVM and optimized CHAID decision tree
Billions of gadgets are already online, making the IoT an essential aspect of daily life.
However, the interconnected nature of IoT devices also leaves them open to cyber threats …
However, the interconnected nature of IoT devices also leaves them open to cyber threats …
Deep learning-based predictive model for defect detection and classification in industry 4.0
In the perspective of the Industry 4.0 (IR 4.0) model, the Deep Learning (DL) domain now
has a significant impact on the production industry. The IR 4.0 model promotes intelligent …
has a significant impact on the production industry. The IR 4.0 model promotes intelligent …
Machine learning-based intrusion detection system for healthcare data
AK Balyan, S Ahuja, SK Sharma… - 2022 IEEE VLSI Device …, 2022 - ieeexplore.ieee.org
The rising advancement of intrusion strategies has given the desperate imperative for
designing and developing IDS with excellent efficiency. The existing IDS have been …
designing and developing IDS with excellent efficiency. The existing IDS have been …
[HTML][HTML] A novel multistage ensemble approach for prediction and classification of diabetes
Diabetes mellitus is a metabolic syndrome affecting millions of people worldwide. Every
year, the rate of occurrence rises drastically. Diabetes-related problems across several vital …
year, the rate of occurrence rises drastically. Diabetes-related problems across several vital …
Defining the “Smart Hospital”: A Literature Review
L Anthopoulos, M Karakidi, D Tselios - World Conference on Information …, 2024 - Springer
Smart hospital grassroots date back to the late 20s when the Information and
Communication Technologies (ICT) started being adopted by the health sector to digitize its …
Communication Technologies (ICT) started being adopted by the health sector to digitize its …
Healthcare Services Enhancement in the Smart City Using 5G
MG Rao, RH Gururaj, H Priyanka, HK Reddy… - … Learning and Privacy …, 2024 - igi-global.com
A smart city is a technologically modern urban area that uses different modes of electronic
methods and sensors to collect specific data. The information collected can be used …
methods and sensors to collect specific data. The information collected can be used …