Application and automation of a clinical statistical method of Kaplan Meyer for prediction of patient's treatment dynamics
- Resource Type
- Conference
- Authors
- Novikov, Vsevolod; Novikova, Anastasia; Mieshkov, Oleksandr; Hotra, Zenon Yu
- Source
- 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET) Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET), 2018 14th International Conference on. :656-659 Feb, 2018
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Signal Processing and Analysis
survival curve
Kaplan Meyer
machine learning
Azure machine learning
- Language
For the prediction purpose of patient's individual treatment effectiveness, the pilot research of the Kaplan Meyer method modification was conducted. As selection data the patient's ultrasound examinations of a gall bladder in five years were used. Processing and the analysis of results had been carried out with the Microsoft Azure Machine learning program using of neuronal networks creation. As criterion for improvement of treatment effectiveness served the absent integral indicator of pathological changes.