Is AI really improving the quality of digital diagnosis

Abstract

The research paper shows how AI's application improves the correctness of diagnosis and increases the rate of accomplishing multiple tasks, including when it comes across some hurdles, such as AI-based digital diagnosis algorithms. In the past, AI was used exclusively to process data, work as an analyzing tool for medical images in health information systems, and assist in decision-making. Still, the process often involves deep machine learning. This is an independent work based on the outcome of other research, which indicates that AI increases bias and needs interaction with people.AI has certain privileges over traditional methods, time and again, relating to swift analysis and comprehensive data assimilation. The patient feedback tells us that despite the preference for AI-generated diagnostic hints, people still want a human professional's supervision or confirmation concerning the results achieved in this sphere, which indicates the directions for the further enhancement of AI utilization in healthcare. These comments emphasize the need to continue improving research and development to address concerns regarding data quality, algorithms' explanations, and ethical problems.

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