Bayesian Analysis of Etiological Factors for Gallbladder Disease
- Indbinding:
- Paperback
- Sideantal:
- 118
- Udgivet:
- 5. marts 2023
- Størrelse:
- 152x7x229 mm.
- Vægt:
- 184 g.
- 2-3 uger.
- 26. november 2024
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- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Bayesian Analysis of Etiological Factors for Gallbladder Disease
Bayesian Analysis of Etiological Factors for Gallbladder Disease by Richa Srivastava explores the use of Bayesian statistical methods to identify risk factors associated with gallbladder disease. The book focuses on the analysis of several demographic, lifestyle, and clinical factors that contribute to the development of the disease.
The book provides a detailed analysis of the factors that influence the probability of developing gallbladder disease, including age, gender, smoking, alcohol consumption, and body mass index. The author uses Bayesian methods to analyze the data and develop models that accurately predict the likelihood of developing the disease based on these factors.
The book also discusses the limitations of traditional statistical methods and highlights the advantages of Bayesian analysis in identifying complex risk factors associated with diseases. This comprehensive analysis of the etiological factors for gallbladder disease is a valuable resource for researchers, clinicians, and public health professionals.
Overall, Bayesian Analysis of Etiological Factors for Gallbladder Disease provides a novel approach to understanding the risk factors associated with the disease and provides insights that can inform prevention and treatment strategies.
The book provides a detailed analysis of the factors that influence the probability of developing gallbladder disease, including age, gender, smoking, alcohol consumption, and body mass index. The author uses Bayesian methods to analyze the data and develop models that accurately predict the likelihood of developing the disease based on these factors.
The book also discusses the limitations of traditional statistical methods and highlights the advantages of Bayesian analysis in identifying complex risk factors associated with diseases. This comprehensive analysis of the etiological factors for gallbladder disease is a valuable resource for researchers, clinicians, and public health professionals.
Overall, Bayesian Analysis of Etiological Factors for Gallbladder Disease provides a novel approach to understanding the risk factors associated with the disease and provides insights that can inform prevention and treatment strategies.
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