Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
[HTML][HTML] A review of the role of machine learning techniques towards brain–computer interface applications
S Rasheed - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
[HTML][HTML] Quantum machine learning architecture for COVID-19 classification based on synthetic data generation using conditional adversarial neural network
Background COVID-19 is a novel virus that affects the upper respiratory tract, as well as the
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
[HTML][HTML] ACCU3RATE: A mobile health application rating scale based on user reviews
Background Over the last decade, mobile health applications (mHealth App) have evolved
exponentially to assess and support our health and well-being. Objective This paper …
exponentially to assess and support our health and well-being. Objective This paper …
[HTML][HTML] Inverted bell-curve-based ensemble of deep learning models for detection of COVID-19 from chest X-rays
Novel Coronavirus 2019 disease or COVID-19 is a viral disease caused by severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of chest X-rays (CXRs) has …
respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of chest X-rays (CXRs) has …
An analysis of explainability methods for convolutional neural networks
Deep learning models have gained a reputation of high accuracy in many domains.
Convolutional Neural Networks (CNN) are specialized towards image recognition and have …
Convolutional Neural Networks (CNN) are specialized towards image recognition and have …
AutoEncoder filter bank common spatial patterns to decode motor imagery from EEG
The present paper introduces a novel method, named AutoEncoder-Filter Bank Common
Spatial Patterns (AE-FBCSP), to decode imagined movements from electroencephalography …
Spatial Patterns (AE-FBCSP), to decode imagined movements from electroencephalography …
An edge-fog computing-enabled lossless EEG data compression with epileptic seizure detection in IoMT networks
The need to improve smart health systems to monitor the health situation of patients has
grown as a result of the spread of epidemic diseases, the ageing of the population, the …
grown as a result of the spread of epidemic diseases, the ageing of the population, the …
[HTML][HTML] A comparison of deep learning techniques for arterial blood pressure prediction
A Paviglianiti, V Randazzo, S Villata, G Cirrincione… - Cognitive …, 2022 - Springer
Continuous vital signal monitoring is becoming more relevant in preventing diseases that
afflict a large part of the world's population; for this reason, healthcare equipment should be …
afflict a large part of the world's population; for this reason, healthcare equipment should be …
[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction
K Barnova, M Mikolasova, RV Kahankova… - Computers in Biology …, 2023 - Elsevier
Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …
brain and the computer. Brain signals contain valuable information about the mental state …