scholarly journals Application Study on the Dynamic Prediction Model for Determining the Mining Subsidence

2016 ◽  
Vol 9 (2) ◽  
pp. 80-85 ◽  
Author(s):  
H. F. HU ◽  
◽  
X. G. LIAN ◽  
Y. LI ◽  
◽  
...  
Keyword(s):  
Prediction Model ◽  
Mining Subsidence ◽  
Dynamic Prediction ◽  
Application Study

Dynamic Prediction Model of Mining Subsidence Based on Cellular Automata

2014 ◽  
Vol 962-965 ◽  
pp. 1056-1061
Author(s):  
Xue Yang Sun ◽  
Yu Cheng Xia
Keyword(s):  
Cellular Automata ◽  
Prediction Model ◽  
Dynamic Model ◽  
Coal Mining ◽  
Mining Subsidence ◽  
Dynamic Evolution ◽  
Dynamic Prediction ◽  
Discrete Dynamic Model ◽  
Coal Mining Subsidence ◽  
Definition Of

Cellular Automata is a discrete dynamic model based on space-time, and is one of the effective methods to study complex systems. The CA, a new method applied to coal mining subsidence dynamic evolution model, provide a new idea for the prediction research of mining subsidence. Definition and basic theory of CA were introduced briefly. According to the particularity of the research in the field of mining subsidence, the definition of CA is extended. The model of dynamic evolution of mining subsidence is built on the CA. Then modeling method and the structure of model are elaborated, and the advantages of the CA are applied to coal mining subsidence prediction model is analyzed.

scholarly journals Dynamic prediction for clinically relevant pancreatic fistula: a novel prediction model for laparoscopic pancreaticoduodenectomy

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Runwen Liu ◽  
Yunqiang Cai ◽  
He Cai ◽  
Yajia Lan ◽  
Lingwei Meng ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pancreatic Fistula ◽  
Postoperative Pancreatic Fistula ◽  
Laparoscopic Pancreaticoduodenectomy ◽  
C Reactive Protein ◽  
Dynamic Prediction ◽  
Albumin Ratio ◽  
Drainage Fluid ◽  
Reactive Protein ◽  
Baseline Factors

Abstract Background With the recent emerge of dynamic prediction model on the use of diabetes, cardiovascular diseases and renal failure, and its advantage of providing timely predicted results according to the fluctuation of the condition of the patients, we aim to develop a dynamic prediction model with its corresponding risk assessment chart for clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy by combining baseline factors and postoperative time-relevant drainage fluid amylase level and C-reactive protein-to-albumin ratio. Methods We collected data of 251 patients undergoing LPD at West China Hospital of Sichuan University from January 2016 to April 2019. We extracted preoperative and intraoperative baseline factors and time-window of postoperative drainage fluid amylase and C-reactive protein-to-albumin ratio relevant to clinically relevant pancreatic fistula by performing univariate and multivariate analyses, developing a time-relevant logistic model with the evaluation of its discrimination ability. We also established a risk assessment chart in each time-point. Results The proportion of the patients who developed clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy was 7.6% (19/251); preoperative albumin and creatine levels, as well as drainage fluid amylase and C-reactive protein-to-albumin ratio on postoperative days 2, 3, and 5, were the independent risk factors for clinically relevant postoperative pancreatic fistula. The cut-off points of the prediction value of each time-relevant logistic model were 14.0% (sensitivity: 81.9%, specificity: 86.5%), 8.3% (sensitivity: 85.7%, specificity: 79.1%), and 7.4% (sensitivity: 76.9%, specificity: 85.9%) on postoperative days 2, 3, and 5, respectively, the area under the receiver operating characteristic curve was 0.866 (95% CI 0.737–0.996), 0.896 (95% CI 0.814–0.978), and 0.888 (95% CI 0.806–0.971), respectively. Conclusions The dynamic prediction model for clinically relevant postoperative pancreatic fistula has a good to very good discriminative ability and predictive accuracy. Patients whose predictive values were above 14.0%, 8.3%, and 7.5% on postoperative days 2, 3, and 5 would be very likely to develop clinically relevant postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.

A dynamic prediction model for time‐to‐peak

2021 ◽  
Author(s):  
Mistaya Langridge ◽  
Ed McBean ◽  
Hossein Bonakdari ◽  
Bahram Gharabaghi
Keyword(s):  
Prediction Model ◽  
Dynamic Prediction ◽  
Time To Peak

scholarly journals S136. A NOVEL APPROACH FOR DEVELOPING PREDICTION MODEL OF TRANSITION TO PSYCHOSIS: DYNAMIC PREDICTION USING JOINT MODELLING

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S378-S379 ◽  
Author(s):  
Hok Pan Yuen ◽  
Andrew Mackinnon ◽  
Jessica Hartmann ◽  
Paul Amminger ◽  
Connie Markulev ◽  
...  
Keyword(s):  
Prediction Model ◽  
Dynamic Prediction ◽  
Joint Modelling ◽  
Novel Approach

scholarly journals Dynamic prediction model to identify young children at high risk of future overweight: Development and internal validation in a cohort study

2020 ◽  
Vol 15 (9) ◽  
Author(s):  
Marieke Welten ◽  
Alet H. Wijga ◽  
Marleen Hamoen ◽  
Ulrike Gehring ◽  
Gerard H. Koppelman ◽  
...  
Keyword(s):  
Cohort Study ◽  
High Risk ◽  
Young Children ◽  
Prediction Model ◽  
Dynamic Prediction ◽  
Internal Validation
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