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HOMEOSTASIS NETWORKS IN PROGNOSIS OF LUNG CANCER PATIENTS SURVIVAL Oleg Kshivets, M.D., Ph.D. Department of Surgery, Siauliai Cancer Center, Lithuania The 9 th  World Conference on Lung Cancer Tokyo, Japan, 2000
Abstract ,[object Object],[object Object],[object Object],[object Object],[object Object]
Samplings: ,[object Object],[object Object],[object Object]
Samplings: ,[object Object],[object Object],[object Object],[object Object]
Radical Procedures: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Main Problem of Analysis of Living Supersystems (e.g. Lung Cancer Patient Homeostasis):  Phenomenon of «Combinatorial Explosion» ,[object Object],[object Object],[object Object]
Basis ,[object Object],[object Object],[object Object],[object Object],[object Object]
Model «Cancer Cells(Cr)- -Human Killer Cells(Kl)» ,[object Object],[object Object],[object Object]
Prognostic Role of Lung Cancer Diameter
Clinicopathologic Nucloids of Lung Cancer Patients with N0-2, n=404
Results of Cluster-Analysis of Clinicopathologic Characteristics of Lung Cancer Patients with N0-2, n=404
Homeostasis Nucloids of Lung Cancer Patients with N0-2, n=404
Results of Cluster-Analysis of Homeostasis Data of Lung Cancer Patients with N0-2, n=404
Results of Correspondence Analysis of Pathologic Characteristics of Lung Cancer Patients with N0-2, n=404
Network-Model of Lung Cancer Patients  with N0-2 (n=404)
Homeostasis Network-Model of Lung Cancer Patients  with N0-2 (n=404)
Morphologic and Homeostasis Network-Model of Lung Cancer Patients  with N0-2 (n=404)
Survival of Lung Cancer Patients with N0-2 (n=404)
Proportional Hazard (Cox) Regression Model of Lung Cancer Patients with N0-2, n=404
Logistic Regression Model of Lung Cancer Patients with N0-2, n=404
Survival of Lung Cancer Patients with N0-2 (n=404)
Survival of Lung Cancer Patients with N1-2 (n=181)
Cluster-Analysis of Data of Early and Invasive Lung Cancer Patients
Phase Transition Early Malignancy into Invasive Cancer
Results of Monte Carlo Simulation:  Phase Transition—Survival of LCP
Regularities between Dynamics Cancer Cell Population and Patient's Survival Rate
Phase Transitions in System «Homeostasis-Malignancy»
The Three Phase Transitions in the System «Malignancy-Human’s Organism»
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 18th Degree Polynomial Fit):   y=a+bx+cx 2 +dx  3 +...
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 18th Degree Polynomial Fit):   y=a+bx+cx 2 +dx  3 +...
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 15th Degree Polynomial Fit):   y=a+bx+cx 2 +dx  3 +...
Cell Ratio Factors in Prognosis of  5-Year Survival Lung Cancer Patients
Results of Monte Carlo Simulation: Cell Ratio Factors—Survival of LCP
Results of Structural Equation Modeling
Networks Between Lung Cancer Patients Survival and System “Cancer- Homeostasis”
Superoncoprognosis-1.0
Conclusions: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Patents: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Patents: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Address: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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