Medicine is not science: guessing the future, predicting the past

Area of Science:

• Epistemology
• Complexity Science
• Medical Informatics

Background:

• Irregularity inherently limits human capacity for knowledge acquisition, understanding, and prediction.
• Classical reductionist scientific approaches struggle with predicting complex systems due to inherent irregularity.

Purpose of the Study:

• To explore the concept of irregularity and its impact on the reliability of knowledge.
• To propose strategies for improving knowledge reliability in the face of irregularity.

Main Methods:

• Conceptual analysis of irregularity and its consequences for knowledge.
• Outline of a naive theory of irregularity.
• Discussion of knowledge systems and expertise development.

Main Results:

• Reliable empirical knowledge historically relies on observed regularities.
• Reducing or increasing regularity enhances knowledge reliability.
• Expertise, intuition, and knowledge systems (e.g., case libraries) improve prediction.

Conclusions:

• Expert judgment and intuition are crucial for diagnosing and treating complex systems, especially in medicine.
• Developing irregularity theory and classification is essential for advancing knowledge.
• Improvements are particularly beneficial in fields with limited feedback for practitioner expertise development.