DE-DSRGs were identified as diagnostic genes for AMI. by Nan Huang (464390)

LASSO-Cox Regression Analysis to Screen Prognosis-Related Genes. by Jie Chu (293795)

The architecture of LSTM cell. by Asmaa Ahmed Awad (16726315)

Image2_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image7_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Table1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.XLSX by Shuo Wang (143908)

Image3_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image6_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image4_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image5_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Graphical overview of the proposed single-cell clustering algorithm. by Jun Seo Ha (15295310)

Table_3_Characterization of spleen and lymph node cell types via CITE-seq and machine learning methods.XLSX by Hao Li (31608)

“…This list was fed into the incremental feature selection (IFS) method, incorporating four classification algorithms (deep forest, random forest, K-nearest neighbor, and decision tree). …”

Table_1_Characterization of spleen and lymph node cell types via CITE-seq and machine learning methods.XLSX by Hao Li (31608)

“…This list was fed into the incremental feature selection (IFS) method, incorporating four classification algorithms (deep forest, random forest, K-nearest neighbor, and decision tree). …”

Table_2_Characterization of spleen and lymph node cell types via CITE-seq and machine learning methods.XLSX by Hao Li (31608)

“…This list was fed into the incremental feature selection (IFS) method, incorporating four classification algorithms (deep forest, random forest, K-nearest neighbor, and decision tree). …”

An inflammation-associated ferroptosis signature can optimize the diagnosis, prognosis evaluation and immunotherapy options in hepatocellular carcinoma by Wanyuan Ruan (13763851)

“…Herein, our aim was to identify the inflammation associated ferroptosis (IAF)- biomarkers for contributing the immunotherapy of HCC.</p> <p>Methods: The train cohort from The Cancer Genome Atlas (TCGA) was clustered into three subtypes (C1, C2, and C3) based on the genes related to inflammation and ferroptosis. …”

Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF by Haidi Wang (9694004)

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity by George S. Watts (7962206)

<i>In silico</i> prediction of blood cholesterol levels from genotype data by Francesco Reggiani (5727733)

“…<div><p>In this work we present a framework for blood cholesterol levels prediction from genotype data. The predictor is based on an algorithm for cholesterol metabolism simulation available in literature, implemented and optimized by our group in the R language. …”

Table1_Construction of predictive model of interstitial fibrosis and tubular atrophy after kidney transplantation with machine learning algorithms.xlsx by Yu Yin (329063)

“…In this study, 13 machine learning algorithms were used to construct IFTA diagnostic models based on necroptosis-related genes.…”