Results 41 to 50 of about 16,211 (118)

A Review on Logistic Regression in Medical Research

National Journal of Community Medicine, 2022
In today’s scenarios many healthcare decisions are being taken by predictive modeling and machine learning techniques. With this review, we focused on logistic regression model, a kind of predictive modeling used in machine learning, and how healthcare ...
Nihar Ranjan Panda
doaj   +1 more source

Predictive Modeling in a VoIP System

Journal of Telecommunications and Information Technology, 2013
An important problem one needs to deal with in a Voice over IP system is server overload. One way for preventing such problems is to rely on prediction techniques for the incoming traffic, namely as to proactively scale the available resources ...
Ana-Maria Simionovici, Alexandru Tantar, Pascal Bouvry, Loic Didelot   +3 more
doaj   +1 more source

Multi-Machine Gaussian Topic Modeling for Predictive Maintenance

IEEE Access, 2021
In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables
Alexander Karlsson, Ebru Turanoglu Bekar, Anders Skoogh   +2 more
doaj   +1 more source

Prediction models in CMI [PDF]

Clinical Microbiology and Infection, 2022
Leibovici, Leonard, Rodríguez-Baño, Jesús, Chemaly, Roy F, Cutler, Sally, Csaki Huttner, Angela, Kalil, Andre C, Leeflang, Mariska, Lina, Gerard, Paul, Mical, Scudeller, Luigia, Tassios, Panayotis T, Yusuf, Erlangga   +11 more
openaire   +5 more sources

Prediction of catastrophes: An experimental model [PDF]

Physical Review E, 2012
Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could ...
Peters, Randall D., Berre, Martine Le, Pomeau, Yves   +2 more
openaire   +3 more sources

Synthesizing benchmarks for predictive modeling [PDF]

2017 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), 2017
Predictive modeling using machine learning is an effective method for building compiler heuristics, but there is a shortage of benchmarks. Typical machine learning experiments outside of the compilation field train over thousands or millions of examples.
Cummins, C, Petoumenos, P, Wang, Z, Leather, H   +3 more
openaire   +6 more sources

Predictive Modeling of Weight Loss and Metabolic Health Outcomes: A Retrospective Predictive Modeling Study

Health Science Reports
Background Obesity is a chronic, complicated, and progressive disease that significantly affects mortality, quality of life, and overall health in nearly 13% of the adult population worldwide.
Rolando Andrade‐Calle, Isabel de laTorre‐Díez, Daniel deLuis‐Román   +2 more
doaj   +1 more source

Acceptance of Automated Social Risk Scoring in the Emergency Department: Clinician, Staff, and Patient Perspectives

Western Journal of Emergency Medicine
Introduction: Healthcare organizations are under increasing pressure from policymakers, payers, and advocates to screen for and address patients’ health-related social needs (HRSN).
Olena Mazurenko, Adam T. Hirsh, Christopher A. Harle, Cassidy McNamee, Joshua R. Vest   +4 more
doaj   +1 more source

Predictive pollen-based biome modeling using machine learning. [PDF]

PLoS ONE, 2018
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published ...
Magdalena K Sobol, Sarah A Finkelstein
doaj   +1 more source

Predictive Model Selection

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1995
SUMMARY We consider the problem of selecting one model from a large class of plausible models. A predictive Bayesian viewpoint is advocated to avoid the specification of prior probabilities for the candidate models and the detailed interpretation of the parameters in each model.
Laud, Purushottam W., Ibrahim, Joseph G.
openaire   +2 more sources