[HTML][HTML] Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods
This paper investigates the applications of explainable AI (XAI) in healthcare, which aims to
provide transparency, fairness, accuracy, generality, and comprehensibility to the results …
provide transparency, fairness, accuracy, generality, and comprehensibility to the results …
Intelligent diagnostic prediction and classification models for detection of kidney disease
Kidney disease is a major public health concern that has only recently emerged. Toxins are
removed from the body by the kidneys through urine. In the early stages of the condition, the …
removed from the body by the kidneys through urine. In the early stages of the condition, the …
Data-driven early diagnosis of chronic kidney disease: development and evaluation of an explainable AI model
PA Moreno-Sánchez - IEEE Access, 2023 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is currently experiencing a growing worldwide incidence
and can lead to premature mortality if diagnosed late, resulting in rising costs to healthcare …
and can lead to premature mortality if diagnosed late, resulting in rising costs to healthcare …
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 …
Using medical data and clustering techniques for a smart healthcare system
With the rapid advancement of information technology, both hardware and software, smart
healthcare has become increasingly achievable. The integration of medical data and …
healthcare has become increasingly achievable. The integration of medical data and …
Dementia prediction using machine learning
Dementia is a chronic and degenerative condition, which has become a major health
concern among the elderly. With ever-continuing cases of dementia, it has become a very …
concern among the elderly. With ever-continuing cases of dementia, it has become a very …
Unsupervised machine learning for disease prediction: a comparative performance analysis using multiple datasets
Purpose Disease risk prediction poses a significant and growing challenge in the medical
field. While researchers have increasingly utilised machine learning (ML) algorithms to …
field. While researchers have increasingly utilised machine learning (ML) algorithms to …
[PDF][PDF] Analysing most efficient deep learning model to detect COVID-19 from computer tomography images
COVID-19 illness has a detrimental impact on the respiratory system, and the severity of the
infection may be determined utilizing a selected imaging technique. Chest computer …
infection may be determined utilizing a selected imaging technique. Chest computer …
Isolation forest with exclusion of attributes based on shapley index
Recognizing anomalies is an extremely important process in data analysis, aimed at
identifying patterns in data that deviate from known norms or typical standards. These …
identifying patterns in data that deviate from known norms or typical standards. These …
Chronic Kidney Disease Prediction using Deep Neural Network
K Jhumka, MM Auzine, MS Casseem… - … Conference on Next …, 2022 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is a global health issue and symptoms are not always visible
at the early stage. Deep learning techniques can be developed to determine the factors that …
at the early stage. Deep learning techniques can be developed to determine the factors that …