Based on the provided text, here is a summary of the proposed doctoral dissertation:

Title: Proposal of a Generalized Model of Platform Architecture for High-Volume Data Processing

Objective:

This research aims to propose a generalized model of platform architecture that can efficiently process large amounts of data, including data acquisition, storage, and presentation.

Research Questions:

• How can we design a cluster architecture that meets the requirements of high-volume data processing?
• What is the optimal number of nodes in the cluster for efficient data processing?
• How can we evaluate the performance of the proposed platform architecture?

 Methodology:

The research will employ various methods, including characterization, hypothesis testing, experimental methods, evaluation, and confirmation of conclusions.

Expected Outcomes:

• A generalized model of platform architecture that meets the requirements of high-volume data processing
• An optimal number of nodes in the cluster for efficient data processing
• A comparison of the performance of the proposed platform architecture with different amounts of data (1TB, 3TB)

Bibliography:

The research will draw from existing literature on big data analytics and processing platforms, healthcare information systems, and software development. 

Expected Results:

The expected results of this research will include:

• A methodology for creating a cluster architecture that meets the requirements of high-volume data processing
• An optimal number of nodes in the cluster for efficient data processing
• A comparison of the performance of the proposed platform architecture with different amounts of data

The proposed doctoral dissertation aims to propose a generalized model of platform architecture that can efficiently process large amounts of data, including data acquisition, storage, and presentation.