... Forest **model** achieved the best (cross-)validated performance to predict ...mortality **risk**, we propose to stratify patients with acute cholangitis into a high and low **risk** ...the **model** ’ s ...

8

... analysis **model**, which is often used for automatic diagnosis of diseases, exploring **risk** factors for causing diseases and predicting the probability of dis- ease occurrence according to **risk** factors, ...

9

... resulting **risk** **prediction** **model** included the variables such as age, gender, individual history of hypertension, individual history of acid regurgitation, first-degree family history of reflux, number ...

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... Abstract: **Risk** **prediction** **model** estimate the **risk** of emerging upcoming outcomes for individual based on several underlying ...high **risk** to expose with the toxicant element which can ...

8

... clinical **risk** **prediction** **model** for BE based on existing data from a large, population-based ...of **risk** factors to predict the presence of BE in patients with GER ...some **risk** factors, ...

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... clinical **risk** **prediction** **model** identifies, four variables affecting the extent of orthodontically induced root resorption which are treatment duration, gender, age and thickness of alveolar ...this ...

5

... lower **risk** of knee ...key **risk** factors at baseline between the two populations, such as age, BMI and injury (Table ...the **model** lost its power to differentiate the cases in hospi- tals, because those ...

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... Some potential limitations of our study have to be discussed. We had to define improved functional out- come after hip arthroscopy (composite of HOS-ADL score above 80 or increase of 23 points). Despite the limitations ...

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... crash **risk** accident ...crash **risk** and do not need to provide an argument ...regression **model** to identify factors caused individual driver **risk** and K-mean cluster algorithm for classification ...

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... d) TSPRG (TSPR Goal) - Internal algorithmic approach for TSPRG attribute is to process CE and DM to develop PSM. Hence PSM shows balanced operations with respect to the project deadline. If project success matrix, PSM = ...

6

... the **model**. Validation sample was used to test the predictive **model** with estimates derived from the **model** of training ...the **risk** **prediction** **model** for breast cancer can be ...

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... a **risk** **prediction** **model** named thyroid malignancy **risk** scoring system (TMRS) for the differential preoperative diagnosis for thyroid cancers (Figure ...

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... There is no single effective parameter to predict clinical outcomes in patients with HF. Therefore, several mod- els have been applied to predict mortality and HF hos- pitalization in patients with HF. In a ...

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... in **risk** **model** development Currently, two sources of bias that arise in developing **risk** **prediction** models from combinations of biomarkers and/or clinical variables are both called “ optimistic ...

6

... the **model** for identifying high-**risk** patients (defined as experiencing $1 hospitalized exacerbations) was assessed with area under the curve (AUC) and receiver operating characteristics analyses, and ...

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... NSCL/P **risk** **prediction** **model** had good specificity, while the sensitivity was not ...correct **prediction** for the NSCL/P cases) and the specificities (the rates of correct **prediction** for ...

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... of **risk** factors provide valuable information on an individual ’ s **risk** trajectory over time and his or her within-person ...of **risk** predictors in the **prediction** of CVD **risk** has been ...

9

... a **risk** **prediction** **model** for BE and EAC combining non-genetic (demographics, lifestyle factors, and GERD symptoms) and genetic ...this **risk** assessment study demonstrate that our combined ...

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... particular **prediction** functions out of some class of plausible alternatives so that, with high reliability, the resulting predictions will be nearly as accurate as possible (“probably approximately ...immediate ...

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... crash **risk** probability **model** called Crash **Risk** **Prediction** ...This **model** is formulated by using traffic parameters ...developed **model** can predict crash risks with appropriate ...

6