✦ LIBER ✦

Predicting the survival of burned patients using discriminant function analysis

✍ Scribed by Clark, G.M.; Volenec, F.J.; Mani, M.M.; Robinson, D.W.; Humphrey, L.J.

Book ID: 122657877
Publisher: Elsevier Science
Year: 1977
Tongue: English
Weight: 415 KB
Volume: 4
Category: Article
ISSN: 0305-4179
DOI: 10.1016/0305-4179(77)90121-8

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Discriminant function analysis of 570 co

Discriminant function analysis of 570 consecutive burns patients admitted to the yorkshire regional burns centre between 1966 and 1973

✍ Moores, B.; Rahman, M.M.; Browning, F.S.C.; Settle, J.A.D. 📂 Article 📅 1975 🏛 Elsevier Science 🌐 English ⚖ 576 KB

Using discriminant function analysis to

Using discriminant function analysis to estimate the impact of a therapeutic intervention in burn care

✍ Lyle Bootman, J.; Wertheimer, A.I.; Zaske, D.; Strate, R.; Solem, L. 📂 Article 📅 1980 🏛 Elsevier Science 🌐 English ⚖ 600 KB

USE OF THE DISCRIMINANT FUNCTION TO PRED

USE OF THE DISCRIMINANT FUNCTION TO PREDICT THE NUMBER OF CONSUMERS WHO DISCRIMINATE

✍ F. M. SCRIVEN; M. F. PETTY 📂 Article 📅 1990 🏛 John Wiley and Sons 🌐 English ⚖ 273 KB

Prediction of coronary events following

Prediction of coronary events following myocardial infarction using a discriminant function analysis

✍ Liang Hsu; Manohara P.J. Senaratne; Sangadasa De-Silva; Richard E. Rossall; Tiss 📂 Article 📅 1986 🏛 Elsevier Science ⚖ 934 KB

Predicting factors of discrimination bet

Predicting factors of discrimination between guilty and innocent: Using a functional data analysis

✍ Kim, D.Y.; Suk, H.W.; Cho, S.; Hwang, H.; Lee, J.H. 📂 Article 📅 2014 🏛 Elsevier Science 🌐 English ⚖ 35 KB

Predicting the survival of patients with

Predicting the survival of patients with breast carcinoma using tumor size

✍ James S. Michaelson; Melvin Silverstein; John Wyatt; Griffin Weber; Richard Moor 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 158 KB 👁 1 views

## Background: Tumor size has long been recognized as the strongest predictor of the outcome of patients with invasive breast carcinoma, although it has not been settled whether the correlation between tumor size and the chance of death is independent of the method of detection, nor is it clear how