Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
[HTML][HTML] Bias investigation in artificial intelligence systems for early detection of Parkinson's disease: A narrative review
Background and Motivation: Diagnosis of Parkinson's disease (PD) is often based on
medical attention and clinical signs. It is subjective and does not have a good prognosis …
medical attention and clinical signs. It is subjective and does not have a good prognosis …
[HTML][HTML] Automated detection of Alzheimer's disease using brain MRI images–a study with various feature extraction techniques
UR Acharya, SL Fernandes, JE WeiKoh… - Journal of medical …, 2019 - Springer
The aim of this work is to develop a Computer-Aided-Brain-Diagnosis (CABD) system that
can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes …
can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes …
Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
Motivation Brain or central nervous system cancer is the tenth leading cause of death in men
and women. Even though brain tumour is not considered as the primary cause of mortality …
and women. Even though brain tumour is not considered as the primary cause of mortality …
Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification
Background Although biopsy is the gold standard for tumour grading, being invasive, this
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …
A pre-trained convolutional neural network based method for thyroid nodule diagnosis
In ultrasound images, most thyroid nodules are in heterogeneous appearances with various
internal components and also have vague boundaries, so it is difficult for physicians to …
internal components and also have vague boundaries, so it is difficult for physicians to …
[HTML][HTML] A customized VGG19 network with concatenation of deep and handcrafted features for brain tumor detection
Brain tumor (BT) is one of the brain abnormalities which arises due to various reasons. The
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
Ultrasound-based differentiation of malignant and benign thyroid Nodules: An extreme learning machine approach
Background and objectives It is important to be able to accurately distinguish between
benign and malignant thyroid nodules in order to make appropriate clinical decisions. The …
benign and malignant thyroid nodules in order to make appropriate clinical decisions. The …
[HTML][HTML] Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network
L Wang, S Yang, S Yang, C Zhao, G Tian… - World journal of surgical …, 2019 - Springer
Background In this study, images of 2450 benign thyroid nodules and 2557 malignant
thyroid nodules were collected and labeled, and an automatic image recognition and …
thyroid nodules were collected and labeled, and an automatic image recognition and …
Data mining technique for automated diagnosis of glaucoma using higher order spectra and wavelet energy features
Eye images provide an insight into important parts of the visual system, and also indicate the
health of the entire human body. Glaucoma is one of the most common causes of blindness …
health of the entire human body. Glaucoma is one of the most common causes of blindness …