S1 Data - by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Parameter settings for algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Parameter settings for algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average runtime of different algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average runtime of different algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Flowchart of GJO-GWO algorithm. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Detailed information of benchmark functions. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Evaluation metrics of the models’ performance. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Detailed information of datasets. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Friedman test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average number of selected features. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Wilcoxon rank sum test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Wilcoxon rank sum test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average number of selected features. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Data_Sheet_1_Optimizing Spatio-Temporal Allocation of the COVID-19 Vaccine Under Different Epidemiological Landscapes.pdf by Wen Cao (696121)

Proposed IDS architecture. by Saad Hammood Mohammed (20623506)

Data_Sheet_1_Determination of phage load and administration time in simulated occurrences of antibacterial treatments.docx by Steffen Plunder (14022498)

DataSheet_2_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC... by Adam D. Irwin (11011752)

“…We set out to demonstrate the feasibility and diagnostic accuracy of pathogen sequencing direct from clinical samples, and estimate the impact of this approach on time to effective therapy when integrated with personalised software-guided antimicrobial dosing in children and adults on ICU with sepsis.</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…”

DataSheet_1_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC... by Adam D. Irwin (11011752)

“…We set out to demonstrate the feasibility and diagnostic accuracy of pathogen sequencing direct from clinical samples, and estimate the impact of this approach on time to effective therapy when integrated with personalised software-guided antimicrobial dosing in children and adults on ICU with sepsis.</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…”

Supplementary Material for: The Therapeutic Evaluation of Steroids in IgA Nephropathy Global (TESTING) Study: Trial Design and Baseline Characteristics by Wong M.G. (11640685)

“…By the time the excess of serious infections was observed, 262 participants had been randomized to the original full-dose treatment algorithm, and an interim analysis was reported in 2016. …”