Clinical Reasoning and Cognitive Errors: Is Artificial Intelligence the Solution?

Introduction:Artificial Intelligence (AI) is the simulation of the human intelligence process bymachines which provides the ability to data analysis, discover relationships, and learn throughcomputer systems. This means machines can mimic human mind reasoning and improve thespeed and accuracy of data processing.Main text: One of the newest fields of AI is the role of AI in health systems for the diagnosis andtreatment of diseases. Clinical decision support systems (CDSS) are computer-based programsthat analyze data to assist healthcare providers in implanting evidence-based clinical guidelinesat the point of care. Clinical decision-making involves a reasoning process in which clinicians ormachines with AI combine different information to present a reasonable conclusion, so that, it isbetter to call it CRSS or clinical reasoning support system.There are two main types of CDSS including: ۱- knowledge-based and ۲- Data-driven. The firsttype analyses the inputs based on the available knowledge from the database and provides appropriateoutcomes such as Up-to-date online medical guidelines.The second type is a kind of machine learning or deep learning. Machine learning is a subsetof AI that uses statistical methods to learn without being explicitly programmed. Deep learningis a subset of machine learning in which artificial neural networks adapt and learn from largeamounts of data.The entrance of AI into medical science and clinical reasoning has several advantages and disadvantages.One of the most important benefits is lowering the rate of heuristic errors and cognitivebiases. Heuristics are mental shortcuts or rule-of-thumb strategies that shorten decision-makingtime but are often fallible because they may cause several types of unconscious errors like availabilityerrors, representation errors, anchoring errors, and confirmation errors.Most cognitive errors are reduced by the assistance of computers, however, some other errors areassociated with the implantation of AI such as base rate neglect. For example, if the software hasbeen designed based on the data from a population in a special geographical region and we wantto apply it in another part of the world, the provided differential diagnoses by the software wouldnot be reasonable since the base rate of diseases are different in various regions and can affect theresults.Also, there are several other pros and cons to the application of AI in medical science such aschallenges to professional ethics.Conclusion: AI was thought to be a solution for heuristic errors, although its usage can be accompaniedby magnifying several biases like algorithm bias, black box bias, base rate neglect,and user-producing data.

کلیدواژه ها:

Clinical Reasoning ، Cognitive Errors ، Artificial Intelligence