Visualization of the RITSS algorithm. by Julian Hecker (758791)

MCnebula: Critical Chemical Classes for the Classification and Boost Identification by Visualization for Untargeted LC–MS/MS Data Analysis by Lichuang Huang (10679028)

Subjects:

MCnebula: Critical Chemical Classes for the Classification and Boost Identification by Visualization for Untargeted LC–MS/MS Data Analysis by Lichuang Huang (10679028)

Subjects:

MCnebula: Critical Chemical Classes for the Classification and Boost Identification by Visualization for Untargeted LC–MS/MS Data Analysis by Lichuang Huang (10679028)

Subjects:

MCnebula: Critical Chemical Classes for the Classification and Boost Identification by Visualization for Untargeted LC–MS/MS Data Analysis by Lichuang Huang (10679028)

Subjects:

Example framework for selecting an appropriate management solution for multi-species/objective forestry management. by Max D. Jones (6269006)

Barley growth during vegetation season in selected representative field-plots. by Tadeáš Fryčák (17811334)

Available habitat across a portion of the study landscape projected for each species type based on selected solutions. by Max D. Jones (6269006)

Visualization of variants. by Dong-Jun Lee (14068673)

Visual and digital scores for P-cadherin, PD-L1 and 5T4. by Sripad Ram (10987346)

Selected Habplan solutions determined via the maximum mean yield/output from Habplan flow files across the projected 35 three-year study period. by Max D. Jones (6269006)

Visualization of the interface workflow. by Nikolai Ufer (11751791)

Unified Noncrossing Multiple Quantile Regressions Tree by Jaeoh Kim (6095708)

aLB cells show high encoding capacity against visual noise across 10 rich environments (cf. Fig 4). by Yijia Yan (49568)

aLB cells show high encoding capacity across 20 rich environments apart from each other. by Yijia Yan (49568)

Data_Sheet_1_Development and Internal Validation of a Disability Algorithm for Multiple Sclerosis in Administrative Data.docx by Ruth Ann Marrie (7384262)

“…<p>Objective: We developed and internally validated an algorithm for disability status in multiple sclerosis (MS) using administrative data.…”

Average accuracy by feature selection method. by Şafak Kılıç (22227019)

“…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”

A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings by Luis de Santiago (5125727)

“…<div><p>Introduction</p><p>The aim of this study is to develop a computer-aided diagnosis system to identify subjects at differing stages of development of multiple sclerosis (MS) using multifocal visual-evoked potentials (mfVEPs). …”

Table 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.docx by Yuxuan Li (1674307)

Image 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.tif by Yuxuan Li (1674307)