Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement by Antoine Falisse (6061601)

“…The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. …”

AGST tool vs. nurse-driven triage. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

VAS triage tool vs. nurse-driven triage. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx by Xinping Lin (1591438)

“…We aim to develop a decision support tool based on machine learning (ML) algorithms, called DAMS (Disability After Mild Stroke), to identify mild stroke patients who would be at high risk of post-stroke disability (PSD) if they only received medical therapy and, more importantly, to aid neurologists in making individual clinical decisions in emergency contexts.…”

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)

“…We aim to develop a decision support tool based on machine learning (ML) algorithms, called DAMS (Disability After Mild Stroke), to identify mild stroke patients who would be at high risk of post-stroke disability (PSD) if they only received medical therapy and, more importantly, to aid neurologists in making individual clinical decisions in emergency contexts.…”

Algorithms and evaluation metrics integrated in the COPS framework. by Teemu J. Rintala (19333003)

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Demographics. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

AGST survey questions. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

Optimal Timings Codebook.xlsx by Emma Spillane (11249121)

Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx by Lian Li (49049)

“…Finally, an online predictive tool based on the optimal model was developed to provide real-time individualized VTE risk predictions for PMN patients.…”

primary ATRT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)

Image 2_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png by Min Liang (363007)

“…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…”

Image 1_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png by Min Liang (363007)

“…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…”

primary mouse RT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

“…The threshold of the minimum number of detected genes was set as the 5th percentile of the distribution of the number of detected genes in all cells while the maximum proportion of mitochondrial genes were set by visual inspection of the plot of the number of detected genes versus the percentage of mitochondrial gene of each sample.scRNA-seq data integration was performed using the CCA-based implemented in Seurat version 3. The clustering was conducted using the graph-based modularity optimization Louvain algorithm implemented in Seurat v3. …”

Table_1_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.XLSX by Qin-Yu Zhao (10014626)

Table_2_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.DOCX by Qin-Yu Zhao (10014626)

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)

“…Five ML methods, Decision Tree (DT), Random Forest (RF), Back Propagation Neural Network (BPNN), Support Vector Machines (SVM), and Tree-based Pipeline Optimization Tool (TPOT), were used to predict the adsorption performance of MOFs. …”

Data_Sheet_3_Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning... by Zheng Luo (284622)