Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis
Q Pei, Y Luo, Y Chen, J Li, D Xie, T Ye - Clinical Chemistry and …, 2022 - degruyter.com
Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …
language recognition, image recognition, natural language processing, and expert systems …
Medical image classification using a light-weighted hybrid neural network based on PCANet and DenseNet
Z Huang, X Zhu, M Ding, X Zhang - Ieee Access, 2020 - ieeexplore.ieee.org
Medical image classification plays an important role in disease diagnosis since it can
provide important reference information for doctors. The supervised convolutional neural …
provide important reference information for doctors. The supervised convolutional neural …
Deep learning for human disease detection, subtype classification, and treatment response prediction using epigenomic data
Deep learning (DL) is a distinct class of machine learning that has achieved first-class
performance in many fields of study. For epigenomics, the application of DL to assist …
performance in many fields of study. For epigenomics, the application of DL to assist …
Improving lung cancer diagnosis by combining exhaled-breath data and clinical parameters
S Kort, M Brusse-Keizer, JW Gerritsen… - ERJ open …, 2020 - Eur Respiratory Soc
Introduction Exhaled-breath analysis of volatile organic compounds could detect lung
cancer earlier, possibly leading to improved outcomes. Combining exhaled-breath data with …
cancer earlier, possibly leading to improved outcomes. Combining exhaled-breath data with …
EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer
L Mirsadeghi, R Haji Hosseini… - BMC Medical …, 2021 - Springer
Background Today, there are a lot of markers on the prognosis and diagnosis of complex
diseases such as primary breast cancer. However, our understanding of the drivers that …
diseases such as primary breast cancer. However, our understanding of the drivers that …
Effects of polycyclic aromatic hydrocarbon exposure and miRNA variations on peripheral blood leukocyte DNA telomere length: a cross-sectional study in Henan …
X Duan, D Zhang, S Wang, X Feng, T Wang… - Science of the Total …, 2020 - Elsevier
Telomeres play a major role in human aging and disease, especially in most cancers.
Telomere length was shortened in workers exposed to polycyclic aromatic hydrocarbons …
Telomere length was shortened in workers exposed to polycyclic aromatic hydrocarbons …
Diagnostic Panel of Three Genetic Biomarkers Based on Artificial Neural Network for Patients With Idiopathic Generalized Epilepsy
A Yabacı Tak, N Tak, F Ilgen Uslu… - Acta Neurologica …, 2024 - Wiley Online Library
The aim of this study is to evaluate the utility of an artificial neural network (ANN) model in
diagnosing idiopathic generalized epilepsy (IGE) and to compare the results of the …
diagnosing idiopathic generalized epilepsy (IGE) and to compare the results of the …
Changes in the expression of genes involved in cell cycle regulation and the relative telomere length in the process of canceration induced by omethoate
X Duan, Y Yang, S Wang, X Feng, T Wang… - Tumor …, 2017 - journals.sagepub.com
Organophosphorous pesticides (OPs), with high efficiency, broad-spectrum and low residue,
are widely used in China. Omethoate is a broad category of organophosphorous pesticides …
are widely used in China. Omethoate is a broad category of organophosphorous pesticides …
Optimal deep belief network with opposition based pity beetle algorithm for lung cancer classification: A DBNOPBA approach
MMMA Priya, SJ Jawhar, JM Geisa - Computer Methods and Programs in …, 2021 - Elsevier
Abstract Background and Objective This research proposes a successful method of
extracting Gray-Level Co-occurrence Matrix (GLCM) picture handling models to classify low …
extracting Gray-Level Co-occurrence Matrix (GLCM) picture handling models to classify low …
Predicting high blood pressure using DNA methylome-based machine learning models
DNA methylation modification plays a vital role in the pathophysiology of high blood
pressure (BP). Herein, we applied three machine learning (ML) algorithms including deep …
pressure (BP). Herein, we applied three machine learning (ML) algorithms including deep …