Ensemble Federated learning approach for diagnostics of multi-order lung cancer
U Subashchandrabose, R John, UV Anbazhagu… - Diagnostics, 2023 - mdpi.com
The early detection and classification of lung cancer is crucial for improving a patient's
outcome. However, the traditional classification methods are based on single machine …
outcome. However, the traditional classification methods are based on single machine …
XGBoost algorithm assisted multi-component quantitative analysis with Raman spectroscopy
Q Wang, X Zou, Y Chen, Z Zhu, C Yan, P Shan… - … Acta Part A: Molecular …, 2024 - Elsevier
To improve prediction performance and reduce artifacts in Raman spectra, we developed an
eXtreme Gradient Boosting (XGBoost) preprocessing method to preprocess the Raman …
eXtreme Gradient Boosting (XGBoost) preprocessing method to preprocess the Raman …
An Intelligent LoRaWAN-based IoT Device for Monitoring and Control Solutions in Smart Farming through anomaly detection integrated with unsupervised machine …
Smart farming, popularly called precision agriculture, refers to technologies like the Internet
of Things (IoT), Artificial Intelligence (AI), and drones that are rapidly transforming age-old …
of Things (IoT), Artificial Intelligence (AI), and drones that are rapidly transforming age-old …
Advances in Artificial Intelligence and Blockchain Technologies for Early Detection of Human Diseases
Modern healthcare should include artificial intelligence (AI) technologies for disease
identification and monitoring, particularly for chronic conditions, including heart, diabetes …
identification and monitoring, particularly for chronic conditions, including heart, diabetes …
[HTML][HTML] An artificial intelligence-based decision support system for early and accurate diagnosis of Parkinson's Disease
Abstract People with Parkinson's Disease (PD) might struggle with sadness, restlessness, or
difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is …
difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is …
A Review on Utilizing Data Mining Techniques for Chronic Kidney Disease Detection
SH Hassan, AM Abdulazeez - The Indonesian Journal of Computer Science, 2024 - ijcs.net
This comprehensive study delves into the application of machine learning (ML) and data
mining techniques for the prognosis and diagnosis of Chronic Kidney Disease (CKD), a …
mining techniques for the prognosis and diagnosis of Chronic Kidney Disease (CKD), a …
Personal AI desktop assistant
TR Mahesh - … Journal of Information Technology, Research and …, 2023 - ijitra.com
Early As we all know, how life is interlinked with the technology and the use of AI. AI-
powered voice assistants have become an integral part of our lives, intertwining technology …
powered voice assistants have become an integral part of our lives, intertwining technology …
Toward explainable deep learning in healthcare through transition matrix and user-friendly features
Modern artificial intelligence (AI) solutions often face challenges due to the “black box”
nature of deep learning (DL) models, which limits their transparency and trustworthiness in …
nature of deep learning (DL) models, which limits their transparency and trustworthiness in …
[HTML][HTML] On the diagnosis of chronic kidney disease using a machine learning-based interface with explainable artificial intelligence
Abstract Chronic Kidney Disease (CKD) is increasingly recognised as a major health
concern due to its rising prevalence. The average survival period without functioning …
concern due to its rising prevalence. The average survival period without functioning …
Deep learning based RAGAE-SVM for Chronic kidney disease diagnosis on internet of health things platform
Chronic kidney disease (CKD) is a prominent disease that causes loss of functionality in the
kidney. Doctors can now more easily gather patient health status data due to the growth of …
kidney. Doctors can now more easily gather patient health status data due to the growth of …