An AI framework to support decisions on GDPR compliance
Abstract The Italian Public Administration (PA) relies on costly manual analyses to ensure
the GDPR compliance of public documents and secure personal data. Despite recent …
the GDPR compliance of public documents and secure personal data. Despite recent …
A review of machine learning techniques for diagnosing Alzheimer's disease using imaging modalities
Alzheimer's disease is a progressive form of dementia. Dementia is a broad term for
conditions that impair memory, thinking, and behaviour. Brain traumas or disorders can …
conditions that impair memory, thinking, and behaviour. Brain traumas or disorders can …
Liver disease classification using histogram-based gradient boosting classification tree with feature selection algorithm
P Theerthagiri - Biomedical Signal Processing and Control, 2025 - Elsevier
Healthcare is the key for everyone to run daily life, and health diagnosing techniques should
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
Liver disease prediction and classification using machine learning techniques
Recently liver diseases are becoming most lethal disorder in a number of countries. The
count of patients with liver disorder has been going up because of alcohol intake, breathing …
count of patients with liver disorder has been going up because of alcohol intake, breathing …
[HTML][HTML] A comparative analysis of boosting algorithms for chronic liver disease prediction
Chronic liver disease (CLD) is a major health concern for millions of people all over the
globe. Early prediction and identification are critical for taking appropriate action at the …
globe. Early prediction and identification are critical for taking appropriate action at the …
Enhancing Disease Diagnosis: Leveraging Machine Learning Algorithms for Healthcare Data Analysis
M Ramteke, S Raut - IETE Journal of Research, 2024 - Taylor & Francis
Healthcare data analysis has emerged as one of the most promising fields of study in recent
years. There are different types of data in the healthcare industry, such as medical test …
years. There are different types of data in the healthcare industry, such as medical test …
Evaluating the Performance of Supervised Machine Learning Algorithms for Predicting Multiple Diseases: A Comparative Study
Machine learning has become one of the most popular and widely used techniques in
various industries, especially in the healthcare sector. This paper focuses on examining the …
various industries, especially in the healthcare sector. This paper focuses on examining the …
High precision eye tracking based on electrooculography (EOG) signal using artificial neural network (ANN) for smart technology application
Electrooculography (EOG) signal is the potential difference between the cornea and the
retina of the eye. The voltage amplitude changes when the eye moves in various directions …
retina of the eye. The voltage amplitude changes when the eye moves in various directions …
[HTML][HTML] Telehealthcare and Covid-19: A noninvasive & low cost invasive, scalable and multimodal real-time smartphone application for early diagnosis of SARS-CoV …
The global coronavirus pandemic overwhelmed many health care systems, enforcing
lockdown and encouraged work from home to control the spread of the virus and prevent …
lockdown and encouraged work from home to control the spread of the virus and prevent …
Towards an Accurate Liver Disease Prediction Based on Two-level Ensemble Stacking Model
The difficulty of detecting liver disease at an early stage goes back to its limited number of
symptoms. In this study, single and ensemble machine learning (ML) algorithms are applied …
symptoms. In this study, single and ensemble machine learning (ML) algorithms are applied …