Explainable artificial intelligence: a comprehensive review
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
Methods Used in Computer‐Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review
SZ Ramadan - Journal of healthcare engineering, 2020 - Wiley Online Library
According to the American Cancer Society's forecasts for 2019, there will be about 268,600
new cases in the United States with invasive breast cancer in women, about 62,930 new …
new cases in the United States with invasive breast cancer in women, about 62,930 new …
A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology
PURPOSE: To develop and test a deep learning based computer-aided diagnosis (CAD)
scheme of mammograms for classifying between malignant and benign masses. METHODS …
scheme of mammograms for classifying between malignant and benign masses. METHODS …
Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm
M Heidari, AZ Khuzani, AB Hollingsworth… - Physics in Medicine …, 2018 - iopscience.iop.org
In order to automatically identify a set of effective mammographic image features and build
an optimal breast cancer risk stratification model, this study aims to investigate advantages …
an optimal breast cancer risk stratification model, this study aims to investigate advantages …
A comparison of computer-aided diagnosis schemes optimized using radiomics and deep transfer learning methods
Objective: Radiomics and deep transfer learning are two popular technologies used to
develop computer-aided detection and diagnosis (CAD) schemes of medical images. This …
develop computer-aided detection and diagnosis (CAD) schemes of medical images. This …
Classification of breast masses using a computer-aided diagnosis scheme of contrast enhanced digital mammograms
Contrast-enhanced digital mammography (CEDM) is a promising imaging modality in breast
cancer diagnosis. This study aims to investigate how to optimally develop a computer-aided …
cancer diagnosis. This study aims to investigate how to optimally develop a computer-aided …
Development and assessment of a new global mammographic image feature analysis scheme to predict likelihood of malignant cases
M Heidari, S Mirniaharikandehei, W Liu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
This study aims to develop and evaluate a new computer-aided diagnosis (CADx) scheme
based on analysis of global mammographic image features to predict likelihood of cases …
based on analysis of global mammographic image features to predict likelihood of cases …
Automatic diagnosis based on spatial information fusion feature for intracranial aneurysm
Timely and accurate auxiliary diagnosis of intracranial aneurysm can help radiologist make
treatment plans quickly, saving lives and cutting costs at the same time. At present, Digital …
treatment plans quickly, saving lives and cutting costs at the same time. At present, Digital …
Applying a random projection algorithm to optimize machine learning model for breast lesion classification
M Heidari, S Lakshmivarahan… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Objective: Since computer-aided diagnosis (CAD) schemes of medical images usually
computes large number of image features, which creates a challenge of how to identify a …
computes large number of image features, which creates a challenge of how to identify a …
Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker
This study aimed to investigate the feasibility of integrating image features computed from
both spatial and frequency domain to better describe the tumor heterogeneity for precise …
both spatial and frequency domain to better describe the tumor heterogeneity for precise …