Artificial Intelligence in Applied Medicine

Abstract

Artificial intelligence (AI) uses advanced language models that employ deep learning techniques to generate responses that imitate human-generated ones when given natural language input. Healthcare staff has concerns regarding the use of artificial intelligence in applied medicine and the response provided by this system may need investigation by expert researchers [1].

The growth of AI in healthcare promises improved diagnostics, personalized treatments, and cost reduction, with potential benefits including equalized access and reduced mortality. However, ethical concerns, regulatory hurdles, and challenges in integrating AI into healthcare must be addressed for its successful revolution in the industry [2].

The utilization of AI in the realm of practical medicine prompts various concerns about bias, transparency, and ethics. AI algorithms may exhibit bias due to biased training data or decision-making processes, resulting in discrepancies in healthcare outcomes. The lack of transparency is a barrier with AI systems, since they often function as opaque entities, rendering it arduous to comprehend the decision-making process. Ethical concerns arise when using AI in the field of applied medicine. [2,3].

Artificial intelligence techniques possess the capability to be used in applied medicine. It is imperative to carry out further well-planned clinical trials before implementing these emerging techniques in a clinical setting.