IM4.0EF: Tele-Medical Realization via Integrating Vague T2NSs with OWCM-RAM Toward Intelligent Medical 4.0 Evaluator Framework

In the modern world, when nearly everyone considers the Internet to be indispensable, there is a constant desire to discover new applications for the technologies that are already in place. As well, recent research has found several synonyms for the adoption of information and communication technology. Industry 4.0, Industry 5.0, and modern technologies are some of these synonyms. Harnessing these technologies in important domains such as medical services and healthcare is vital. Wherein, the medical field has undergone changes, going from version 1.0 to version 4.0 currently. Medical 4.0 represents a significant advancement in medical practices and systems, leveraging cutting-edge digital technology, data analytics, automation, and artificial intelligence (AI) within the healthcare sector. Therefore, it is essential to give priority to important enabling aspects (EAs) that influence these cutting-edge technologies adoption into the healthcare industry in a methodical and successful manner. Inspired by these facts, the prioritizing of the determined EAs is robust motivator in this study. Hence, we constructed intelligent Medical 4.0 evaluator framework (IM4.0EF) which responsible for prioritizing EAs based in a set of benchmarks (Bs) through leveraging Opinion Weight Criteria Method (OWCM) as a novel multi-criteria decision-making (MCDM) technique to obtain benchmarks’ weights. Wherein these weights are utilized in Root Assessment Method (RAM) as a novel MCDM to rank EAs and recommending the most influence and optimal EA as well as the worst EA.