Literature DB >> 16522430

Methods of clinical prediction.

William A Grobman1, David M Stamilio.   

Abstract

The ability to predict clinical outcomes is of great importance to physicians and patients alike. Accordingly, multiple different methods have been used in an effort to accurately predict these outcomes. These methods include the development of scoring systems based on univariable and multivariable analysis, as well as models involving the use of neural network, nomograms, and classification and regression trees. The principles of these types of methods, as well as their advantages and disadvantages will be presented.

Entities:  

Mesh:

Year:  2006        PMID: 16522430     DOI: 10.1016/j.ajog.2005.09.002

Source DB:  PubMed          Journal:  Am J Obstet Gynecol        ISSN: 0002-9378            Impact factor:   8.661


  19 in total

1.  Quantitative assessment of abdominal aortic aneurysm geometry.

Authors:  Judy Shum; Giampaolo Martufi; Elena Di Martino; Christopher B Washington; Joseph Grisafi; Satish C Muluk; Ender A Finol
Journal:  Ann Biomed Eng       Date:  2010-10-02       Impact factor: 3.934

Review 2.  Developing an international register of clinical prediction rules for use in primary care: a descriptive analysis.

Authors:  Claire Keogh; Emma Wallace; Kirsty K O'Brien; Rose Galvin; Susan M Smith; Cliona Lewis; Anthony Cummins; Grainne Cousins; Borislav D Dimitrov; Tom Fahey
Journal:  Ann Fam Med       Date:  2014-07       Impact factor: 5.166

3.  Clinical measures identify vitamin D deficiency in dialysis.

Authors:  Ishir Bhan; Sherri-Ann M Burnett-Bowie; Jun Ye; Marcello Tonelli; Ravi Thadhani
Journal:  Clin J Am Soc Nephrol       Date:  2010-02-25       Impact factor: 8.237

4.  Clinical decision rule for primary care patient with acute low back pain at risk of developing chronic pain.

Authors:  Wolf E Mehling; Mark H Ebell; Andrew L Avins; Frederick M Hecht
Journal:  Spine J       Date:  2015-03-13       Impact factor: 4.166

5.  Early lactate clearance for predicting active bleeding in critically ill patients with acute upper gastrointestinal bleeding: a retrospective study.

Authors:  Tomoki Wada; Akiyoshi Hagiwara; Tatsuki Uemura; Naoki Yahagi; Akio Kimura
Journal:  Intern Emerg Med       Date:  2016-02-02       Impact factor: 3.397

6.  PREOP-Gallstones: A Prognostic Nomogram for the Management of Symptomatic Cholelithiasis in Older Patients.

Authors:  Abhishek D Parmar; Kristin M Sheffield; Deepak Adhikari; Robert A Davee; Gabriela M Vargas; Nina P Tamirisa; Yong-Fang Kuo; James S Goodwin; Taylor S Riall
Journal:  Ann Surg       Date:  2015-06       Impact factor: 12.969

7.  Prediction of periventricular leukomalacia. Part II: Selection of hemodynamic features using computational intelligence.

Authors:  Biswanath Samanta; Geoffrey L Bird; Marijn Kuijpers; Robert A Zimmerman; Gail P Jarvik; Gil Wernovsky; Robert R Clancy; Daniel J Licht; J William Gaynor; Chandrasekhar Nataraj
Journal:  Artif Intell Med       Date:  2009-01-21       Impact factor: 5.326

8.  Risk factors at birth for permanent obstetric brachial plexus injury and associated osseous deformities.

Authors:  Rahul K Nath; Nirupama Kumar; Meera B Avila; Devin K Nath; Sonya E Melcher; Mitchell G Eichhorn; Chandra Somasundaram
Journal:  ISRN Pediatr       Date:  2012-02-01

9.  Risk factors of dystocia in nulliparous women.

Authors:  Rahele Alijahan; Masoumeh Kordi
Journal:  Iran J Med Sci       Date:  2014-05

10.  Simple Scoring System and Artificial Neural Network for Knee Osteoarthritis Risk Prediction: A Cross-Sectional Study.

Authors:  Tae Keun Yoo; Deok Won Kim; Soo Beom Choi; Ein Oh; Jee Soo Park
Journal:  PLoS One       Date:  2016-02-09       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.