A systematic review on supervised and unsupervised machine learning algorithms for data science
Abstract Machine learning is as growing as fast as concepts such as Big data and the field of
data science in general. The purpose of the systematic review was to analyze scholarly …
data science in general. The purpose of the systematic review was to analyze scholarly …
Strengths, weaknesses, opportunities, and threats analysis of artificial intelligence and machine learning applications in radiology
Currently, the use of artificial intelligence (AI) in radiology, particularly machine learning
(ML), has become a reality in clinical practice. Since the end of the last century, several ML …
(ML), has become a reality in clinical practice. Since the end of the last century, several ML …
[BUKU][B] Supervised and unsupervised learning for data science
Supervised and unsupervised learning algorithms have shown a great potential in
knowledge acquisition from large data sets. Supervised learning reflects the ability of an …
knowledge acquisition from large data sets. Supervised learning reflects the ability of an …
Impact of machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy and survival …
Purpose The aim of this study was to assess the potential of machine learning with
multiparametric magnetic resonance imaging (mpMRI) for the early prediction of …
multiparametric magnetic resonance imaging (mpMRI) for the early prediction of …
MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma
L Zhao, J Gong, Y **, M Xu, C Li, X Kang, Y Yin… - European …, 2020 - Springer
Objectives To establish and validate a radiomics nomogram for prediction of induction
chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients …
chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients …
Predicting outcome of endovascular treatment for acute ischemic stroke: potential value of machine learning algorithms
Background: Endovascular treatment (EVT) is effective for stroke patients with a large vessel
occlusion (LVO) of the anterior circulation. To further improve personalized stroke care, it is …
occlusion (LVO) of the anterior circulation. To further improve personalized stroke care, it is …
Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients
H Dammu, T Ren, TQ Duong - Plos one, 2023 - journals.plos.org
The goal of this study was to employ novel deep-learning convolutional-neural-network
(CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and …
(CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and …
Multiparametric magnetic resonance imaging for predicting pathological response after the first cycle of neoadjuvant chemotherapy in breast cancer
Objectives The purpose of this study was to determine whether multiparametric magnetic
resonance imaging (MRI) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion …
resonance imaging (MRI) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion …
Update on DWI for breast cancer diagnosis and treatment monitoring
DWI is a noncontrast MRI technique that measures the diffusion of water molecules within
biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations …
biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations …
Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre-and early treatment predicts pathologic complete response
Purpose This study used machine learning classification of texture features from MRI of
breast tumor and peri-tumor at multiple treatment time points in conjunction with molecular …
breast tumor and peri-tumor at multiple treatment time points in conjunction with molecular …