[HTML][HTML] Deep learning with radiomics for disease diagnosis and treatment: challenges and potential
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
[HTML][HTML] Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Explainable deep learning for pulmonary disease and coronavirus COVID-19 detection from X-rays
Abstract Background and Objective: Coronavirus disease (COVID-19) is an infectious
disease caused by a new virus never identified before in humans. This virus causes …
disease caused by a new virus never identified before in humans. This virus causes …
Automatic detection of Alzheimer's disease progression: An efficient information fusion approach with heterogeneous ensemble classifiers
Predicting Alzheimer's disease (AD) progression is crucial for improving the management of
this chronic disease. Usually, data from AD patients are multimodal and time series in …
this chronic disease. Usually, data from AD patients are multimodal and time series in …
Efficient framework for brain tumour classification using hierarchical deep learning neural network classifier
In this manuscript, an efficient framework is proposed for brain tumour classification (BTC)
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
Detecting SARS-CoV-2 from chest X-Ray using artificial intelligence
Chest radiographs (X-rays) combined with Deep Convolutional Neural Network (CNN)
methods have been demonstrated to detect and diagnose the onset of COVID-19, the …
methods have been demonstrated to detect and diagnose the onset of COVID-19, the …
Deep learning for image-based mobile malware detection
F Mercaldo, A Santone - Journal of Computer Virology and Hacking …, 2020 - Springer
Current anti-malware technologies in last years demonstrated their evident weaknesses due
to the signature-based approach adoption. Many alternative solutions were provided by the …
to the signature-based approach adoption. Many alternative solutions were provided by the …
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
Purpose To perform a systematic review on the research on the application of artificial
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …
Radiomic features for prostate cancer grade detection through formal verification
A Santone, MC Brunese, F Donnarumma… - La radiologia …, 2021 - Springer
Aim Prostate cancer represents the most common cancer afflicting men. It may be
asymptomatic at the early stage. In this paper, we propose a methodology aimed to detect …
asymptomatic at the early stage. In this paper, we propose a methodology aimed to detect …
Machine learning for coronavirus covid-19 detection from chest x-rays
At the end of 2019, a new form of Coronavirus, called COVID-19, has widely spread in the
world. To quickly screen patients with the aim to detect this new form of pulmonary disease …
world. To quickly screen patients with the aim to detect this new form of pulmonary disease …