Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
A review of explainable and interpretable AI with applications in COVID‐19 imaging
The development of medical imaging artificial intelligence (AI) systems for evaluating COVID‐
19 patients has demonstrated potential for improving clinical decision making and assessing …
19 patients has demonstrated potential for improving clinical decision making and assessing …
[HTML][HTML] A deep learning architecture for multi-class lung diseases classification using chest X-ray (CXR) images
In 2019, the world experienced the rapid outbreak of the Covid-19 pandemic creating an
alarming situation worldwide. The virus targets the respiratory system causing pneumonia …
alarming situation worldwide. The virus targets the respiratory system causing pneumonia …
CSwin-PNet: A CNN-Swin Transformer combined pyramid network for breast lesion segmentation in ultrasound images
H Yang, D Yang - Expert Systems with Applications, 2023 - Elsevier
Currently, the automatic segmentation of breast tumors based on breast ultrasound (BUS)
images is still a challenging task. Most lesion segmentation methods are implemented …
images is still a challenging task. Most lesion segmentation methods are implemented …
Machine learning tools for long-term type 2 diabetes risk prediction
A steady rise has been observed in the percentage of elderly people who want and are still
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
[HTML][HTML] Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis
In this paper, we study human–AI collaboration protocols, a design-oriented construct aimed
at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We …
at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We …
A generic deep learning framework to classify thyroid and breast lesions in ultrasound images
Breast and thyroid cancers are the two common cancers to affect women worldwide.
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …
Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records
Background and objective Cardiac arrhythmia, which is an abnormal heart rhythm, is a
common clinical problem in cardiology. Detection of arrhythmia on an extended duration …
common clinical problem in cardiology. Detection of arrhythmia on an extended duration …
[HTML][HTML] Machine learning in clinical decision making
Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …
Hemorrhage detection based on 3D CNN deep learning framework and feature fusion for evaluating retinal abnormality in diabetic patients
S Maqsood, R Damaševičius, R Maskeliūnas - Sensors, 2021 - mdpi.com
Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and
accurate diagnosis can improve the analysis and prognosis of the disease. One of the …
accurate diagnosis can improve the analysis and prognosis of the disease. One of the …