Image 10_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Table 2_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.xlsx by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Table 3_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Image 4_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Data Sheet 1_EFTUD2 is a promising diagnostic and prognostic indicator involved in the tumor immune microenvironment and glycolysis of lung adenocarcinoma.docx by Ankang Yin (20970515)

“…Hub genes related to EFTUD2 were identified through topological algorithms, and immune infiltration was assessed using CIBERSORT. …”

Data_Sheet_3_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…Objective<p>The aim of this investigation was to assess the diagnostic and therapeutic efficacy of G2 and S-phase expressed 1 (GTSE1) in lung adenocarcinoma (LUAD), while examining its impact on immune infiltration and drug treatment mechanisms.…”

Table 7_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Data_Sheet_1_Comprehensive analysis of the diagnostic and therapeutic value, immune infiltration, and drug treatment mechanisms of GTSE1 in lung adenocarcinoma.docx by Guanqiang Yan (18472116)

“…Objective<p>The aim of this investigation was to assess the diagnostic and therapeutic efficacy of G2 and S-phase expressed 1 (GTSE1) in lung adenocarcinoma (LUAD), while examining its impact on immune infiltration and drug treatment mechanisms.…”

Table 5_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.docx by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Image 9_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Table 6_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.xlsx by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Image 1_Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.tif by Dong Pan (1835707)

“…Additionally, DCE-MRI data from 101 patients in The Cancer Imaging Archive were used to extract radiomic features from early- and delayed-phase images. A STAT3 predictive model was developed using six machine learning algorithms. …”

Image 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Image 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Data Sheet 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Image 3_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Table 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.xlsx by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Data Sheet 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)

“…Korea is entering a super-aged phase, yet few approaches have used nationally representative survey data.…”

Polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…The Perdew-Burke-Ernzerhof (PBE) functional with Hubbard-U corrections were applied was utilized for all calculations. …”

FCP dataset for forecasting temperature, PV, price, and load by Hanwen Zhang (18259666)

“…One of the key actions is to phase out Internal Combustion Engine (ICE) vehicles and significantly expand electric vehicle (EV) adoption. …”