Data Sheet 7_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Table 1_Multiparametric-MRI habitat radiomics analysis for discriminating pathological types of brain metastases.docx by Jinling Zhu (15920747)

“…This study aimed to evaluate the potential of multiparametric MRI (mpMRI)-based habitat radiomics analysis in differentiating the pathological types of BMs.…”

Data Sheet 9_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Data Sheet 2_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Data Sheet 1_Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis.csv by Zohreh Javanmard (20270430)

“…Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study’s systematic review and meta-analysis.…”

Data Sheet 6_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Data Sheet 1_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.pdf by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Data Sheet 4_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Data Sheet 8_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Table 1_Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis.docx by Zohreh Javanmard (20270430)

“…Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study’s systematic review and meta-analysis.…”

Table 2_Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis.docx by Zohreh Javanmard (20270430)

“…Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study’s systematic review and meta-analysis.…”

Data Sheet 5_Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups.xlsx by Seyoung Mun (591565)

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”

Optical Tactile (TacTip) Dataset for texture classification by Dexter Shepherd (13238508)

“…We have two parts of this dataset "X_data_15" and "X_data_gel_15". The first one is a sensor that uses clear silicone, and the second makes use of a clear gel. …”

Phenotyping of children with abdominal pain. by 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 by 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 by 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 by 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 by 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 by Dexter Shepherd (13238508)

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

Massive Mixed Models in Julia by Phillip M. Alday (2814652)

“…<br><br>As a demonstration of the capabilities that Julia unlocks in this domain, I will present a model fit to the MovieLens (Harper and Konstan, 2015) data containing 32 million observations and partially crossed random effects with 200,948 and 87,585 levels. …”