Data Sheet 1_Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical tri... حسب Caio César Souza Conceição (21232238)

"…LASSO and CombiROC were used to select optimal predictive variables. The Youden criteria identified the best threshold for different variable combinations, which were then compared based on the highest area under the curve (AUC) and accuracy. …"

Table 1_Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial.xl... حسب Caio César Souza Conceição (21232238)

"…LASSO and CombiROC were used to select optimal predictive variables. The Youden criteria identified the best threshold for different variable combinations, which were then compared based on the highest area under the curve (AUC) and accuracy. …"

Phenotyping of children with abdominal pain. حسب Kazuya Takahashi (69459)

"…The color of each branch indicates the number of data points (cluster size), as shown in the color bar on the right. …"

Table 2_Association between frailty and pain in older people at high risk of future hospitalization.docx حسب Huan-Ji Dong (9427462)

"…</p>Methods<p>High risk of hospitalization was identified using case-finding algorithm including 32 diagnostic codes of morbidities and healthcare use. …"

Table 3_Association between frailty and pain in older people at high risk of future hospitalization.docx حسب Huan-Ji Dong (9427462)

"…</p>Methods<p>High risk of hospitalization was identified using case-finding algorithm including 32 diagnostic codes of morbidities and healthcare use. …"

Table 1_Association between frailty and pain in older people at high risk of future hospitalization.docx حسب Huan-Ji Dong (9427462)

"…</p>Methods<p>High risk of hospitalization was identified using case-finding algorithm including 32 diagnostic codes of morbidities and healthcare use. …"

Table 4_Association between frailty and pain in older people at high risk of future hospitalization.docx حسب Huan-Ji Dong (9427462)

"…</p>Methods<p>High risk of hospitalization was identified using case-finding algorithm including 32 diagnostic codes of morbidities and healthcare use. …"

Electrical Tactile Dataset (Piezoelectric and Accelerometer) for textures حسب Dexter Shepherd (13238508)

"…Python users can load in the dataset using the code provided in the ReadMe.</p>…"

IDWE_CHM (NRT_L) حسب Hao Chen (11770646)

"…</p><p dir="ltr">For a comprehensive description of the project, please refer to:<br><b>An Incremental Dynamic Weighting Ensemble Framework for Long-Term and NRT Precipitation Prediction</b><br><a href="https://figshare.com/projects/An_Incremental_Dynamic_Weighting_Ensemble_Framework_for_Long-Term_and_NRT_Precipitation_Prediction/241619" rel="noreferrer" target="_blank">https://figshare.com/projects/An_Incremental_Dynamic_Weighting_Ensemble_Framework_for_Long-Term_and_NRT_Precipitation_Prediction/241619</a></p><p><br></p><p dir="ltr">The IDWE_CHM dataset provides <b>four precipitation variables</b>, all derived from the ensemble framework but with slightly different modeling approaches:</p><ul><li><b>ENS_Reg</b> – A purely regression-based merged precipitation estimate. This product is generated by optimally weighting and combining the input datasets (ERA5-Land, IMERG, GSMaP, etc.) using regression, without additional classification. …"

Image 4_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.pdf حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Image 1_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.tif حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Image 7_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.tif حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Data Sheet 1_Plasma methylated HIST1H3G as a non-invasive biomarker for diagnostic modeling of hepatocellular carcinoma.zip حسب Weiwei Zhu (251527)

"…HIST1H3G, PIVKA-II, total bilirubin (TBIL) and age were selected as the optimal markers and were included in the development of a diagnostic model. …"

Data Sheet 1_Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer.docx حسب Jianguang Lin (13032527)

"…Accurately predicting tumor radiosensitivity is critical for optimizing therapeutic outcomes and personalizing treatment strategies. …"

Data Sheet 1_Triglyceride-glucose index and mortality in congestive heart failure with diabetes: a machine learning predictive model.doc حسب Lin Yu (221619)

"…The predictive performance was evaluated using seven machine learning algorithms, with the Random Survival Forest (RSF) algorithm achieving the best performance (AUC=0.817).…"

Image 2_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.pdf حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

IDWE_CHM (NRT_F) حسب Hao Chen (11770646)

"…</p><p dir="ltr">For a comprehensive description of the project, please refer to:<br><b>An Incremental Dynamic Weighting Ensemble Framework for Long-Term and NRT Precipitation Prediction</b><br><a href="https://figshare.com/projects/An_Incremental_Dynamic_Weighting_Ensemble_Framework_for_Long-Term_and_NRT_Precipitation_Prediction/241619" rel="noreferrer" target="_blank">https://figshare.com/projects/An_Incremental_Dynamic_Weighting_Ensemble_Framework_for_Long-Term_and_NRT_Precipitation_Prediction/241619</a></p><p><br></p><p dir="ltr">The IDWE_CHM dataset provides <b>four precipitation variables</b>, all derived from the ensemble framework but with slightly different modeling approaches:</p><ul><li><b>ENS_Reg</b> – A purely regression-based merged precipitation estimate. This product is generated by optimally weighting and combining the input datasets (ERA5-Land, IMERG, GSMaP, etc.) using regression, without additional classification. …"

Image 3_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.pdf حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Table 1_Plasma methylated HIST1H3G as a non-invasive biomarker for diagnostic modeling of hepatocellular carcinoma.docx حسب Weiwei Zhu (251527)

"…HIST1H3G, PIVKA-II, total bilirubin (TBIL) and age were selected as the optimal markers and were included in the development of a diagnostic model. …"

Data Sheet 1_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.zip حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"