Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.X... by Fang Tian (360682)

Total primary energy demand by fuel in China. by Da Lian (18880882)

Table_3_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.docx by Lei Chen (54296)

Table_2_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.docx by Lei Chen (54296)

Table_1_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.xlsx by Lei Chen (54296)

Table_1_Screening of Long Non-coding RNAs Biomarkers for the Diagnosis of Tuberculosis and Preliminary Construction of a Clinical Diagnosis Model.docx by Juli Chen (12187358)

“…Background<p>Pathogenic testing for tuberculosis (TB) is not yet sufficient for early and differential clinical diagnosis; thus, we investigated the potential of screening long non-coding RNAs (lncRNAs) from human hosts and using machine learning (ML) algorithms combined with electronic health record (EHR) metrics to construct a diagnostic model.…”

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Consort diagram for the study. by Nicola Lazzarini (3528197)

Subjects:

Performance confidence intervals. by Nicola Lazzarini (3528197)

Subjects:

Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

Subjects:

Input features. by Nicola Lazzarini (3528197)

Subjects:

Most important predictive features. by Nicola Lazzarini (3528197)

Subjects:

Age feature importance. by Nicola Lazzarini (3528197)

Subjects:

Machine learning vs. clinicians. by Nicola Lazzarini (3528197)

Subjects:

ROC curves. by Nicola Lazzarini (3528197)

Subjects:

PR curves. by Nicola Lazzarini (3528197)

Subjects:

Overview of the cohort definition process. by Nicola Lazzarini (3528197)

Subjects:

Automatic Machine Learning Combined with High-Throughput Computational Screening of Hydrophobic Metal–Organic Frameworks for Capture of Methanol and Ethanol from the Air by Lulu Zhang (104611)

“…The accuracy of the ML model was further improved using the random search method. …”

Decision tree*. by Gabrielle Bonnet (11614471)

Table_1_One-Time Optimization of Advanced T Cell Culture Media Using a Machine Learning Pipeline.DOCX by Paul Grzesik (11136582)

“…When optimizing culture media for primary cells used in cell and gene therapy, traditional DoE approaches that depend on interpretable models will not always provide reliable predictions due to high donor variability. …”