Graphical correlation of visual and strip reader IU values. by Ernest L. Yufenyuy (12494849)

Performance of five machine learning algorithms with leave-one-out cross validation using 46 CRKP and 49 CSKP mass spectra, in terms of accuracy, sensitivity and specificity for di... by Tsi-Shu Huang (139709)

Distribution of reader values in IU for (A) positive verification line (PVL) for HIV-positive and negative specimens and B) long-term line (LTL) for HIV-1 recent and long-term spec... by Ernest L. Yufenyuy (12494849)

Table 2 - by Ernest L. Yufenyuy (12494849)

Two-by-two tables comparing EIA/Western Blot based final HIV diagnostic results with A) visual interpretation for the positive verification line and B) hand-held reader-based inter... by Ernest L. Yufenyuy (12494849)

DataSheet_1_Development of a diagnostic algorithm to ascertain malignant pleural effusion utilizing clinical indicators and serum metal concentrations.xlsx by Jinling Ji (18815896)

Spectral information of ASTER bands used. by Gabriel Prates Hallal (19555976)

“…The signature was resampled to be compatible with the Advanced Spaceborne Thermal Emission Radiometer (ASTER) sensor bandwidth values and used as a reference endmember for the Spectral Angle Mapper (SAM) and Linear Spectral Unmixing (LSU) digital image classification algorithms. …”

Supplementary Material for: Prediction Model of Cardiac Risk for Dental Extraction in Elderly Patients with Cardiovascular Diseases by Tang M. (3707437)

“…When the RF model was constructed, its overall classification accuracy was 0.82 at the optimal cutoff value of 18.5%. …”

Cohort attrition diagram. by Vitaly Lorman (16814000)

“…Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. …”

Cohort demographic and clinical characteristics. by Vitaly Lorman (16814000)

“…Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. …”

Histogram of cohort entry dates. by Vitaly Lorman (16814000)

“…Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. …”

Data_Sheet_1_An exploration on the machine-learning-based stroke prediction model.ZIP by Shenshen Zhi (18458547)

Data Sheet 1_Real-world data-driven early warning system for risk-stratified liver injury in hospitalized COVID-19 patients—Machine learning models for clinical decision support.do... by Yuanguo Xiong (20135991)

“…The online prediction platforms were developed for liver injury early warning risk stratification (low- and high-risk) based on predicted probabilities classification.</p>Conclusion<p>This research successfully established a machine learning-powered early warning system capable of real-time risk stratification for COVID-19-associated liver injury through dynamic integration of clinical data. …”

Data_Sheet_1_Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU.docx by Elham Jamshidi (11013993)

“…</p><p>Objectives: Early prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission.…”

Data_Sheet_1_Predictive models for endoscopic disease activity in patients with ulcerative colitis: Practical machine learning-based modeling and interpretation.pdf by Xiaojun Li (138162)

“…In addition, the above three variables had a more balanced contribution to each classification under the MES than the UCEIS according to the SHAP values.…”

DataSheet_1_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal chola... by Di Wang (329735)