<b>A Primary Care Guide to the Screening and Pharmacologic Management of Chronic Kidney Disease in People Living With Type 2 Diabetes</b> by Eugene E. Wright (21500539)

“…<p dir="ltr">This paper reports the expert opinions and recommendations made by primary care physicians (PCPs) to optimize screening and management of chronic kidney disease (CKD) associated with diabetes and presents algorithms to provide a practical and simplified guide for PCPs. …”

Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”

RNN performance comparison with/out optimization. by Muhammad Usman Tariq (11022141)

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”

Parameter settings. by Yang Cao (53545)

“…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …”

Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf by Yuwen Lyu (14330781)

“…Objective<p>Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. …”

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

“…Liquid fermentation is the primary method for GA₃ production usingFusarium fujikuroi. …”

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

“…Liquid fermentation is the primary method for GA₃ production usingFusarium fujikuroi. …”

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

“…Liquid fermentation is the primary method for GA₃ production usingFusarium fujikuroi. …”

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

“…Liquid fermentation is the primary method for GA₃ production usingFusarium fujikuroi. …”

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

“…Liquid fermentation is the primary method for GA₃ production usingFusarium fujikuroi. …”

Overview of study assessments of the trial. by Tan Boon Toh (1348143)

“…Established PDOs will be subject to QPOP analyses to determine their therapeutic sensitivities to specific panels of drugs. A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. …”

MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

“…Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …”

Table_1_Deep learning-based classification system of bacterial keratitis and fungal keratitis using anterior segment images.DOCX by Yeo Kyoung Won (15599561)

Image_4_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... by Di Wang (329735)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

Image_5_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... by Di Wang (329735)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

Image_3_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... by Di Wang (329735)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

Image_1_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... by Di Wang (329735)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

Image_2_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... by Di Wang (329735)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

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)

“…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …”

Proposed method approach. by Muhammad Usman Tariq (11022141)

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”