Real-World Data

In the metaverse healthcare, artificial intelligence (AI) and big data analytics are two crucial elements.

To do big data analytics, it is indispensable to build up health information system for holding big data in the cloud with or without federated training system by integrating multi-source data from individual, household, school, institution, community, region, country, until globe.

Figures illustrate Web-based information system on Taiwan national cancer screening program. Figures show a series of on-site community-based integrated screening programs in Taiwan to become complementary role with national cancer screening program.

These include integrated data on a series of cancers and chronic diseases at population level. population-based data These also include how to build up population-based proband-oriented pedigree information system.

Digital Bank

In addition to have big data on population-based electric health record, if we want to have complete real-world data, it has to be perspective for having digital bank. The digital bank may consist of biobank (such as blood sample, DNA, and microbiota) and imaging profiles like digital mammography.

Basic Model

In parallel with evidence-based health care phase with RCT trials, a series of colorectal cancer service screening program, particularly FIT test, have been conducted.

To make adjustment for lead-time and self-selection bias (arising from screening cecal intubation rate), several analytical models are adopted. Figures show a series of demonstrations using previous studies on national screening program in Taiwan.

Personalized Model

One of 4P principle for colorectal cancer screening is to develop personalized risk assessment model for developing screening strategy.

As such a risk assessment is dynamic, personalized instance risk assessment model is therefore required. It begins with a three-state Markov machine learning model for occurrence of PCDP and the transition from PCDP to clinical phase.