Department of Internal Medicine II and Gastroenterology, Carol Davila University of Medicine and Pharmacy Bucharest; Department of Gastroenterology, Emergency University Hospital Bucharest, Romania. .
J Gastrointestin Liver Dis. 2022 Jun 12;31(2):244-253. doi: 10.15403/jgld-4180.
Artificial intelligence (AI) is not a new idea or field of research. However, recent advancements in computing technology as well as increasing worldwide experience in applying AI to various fields have enabled us to hope that applying it to the medical practice could improve outcomes. The aim of the article was to evaluate potential applications of artificial intelligence (AI) in the clinical practice of gastroenterology. AI algorithms can offer many benefits over the traditional diagnostic, prognostic, therapeutic scores, or non-AI enhanced procedures that we perform today. It can very easily process complex mathematical data, which would allow to account for many parameters and with highly sophisticated formulas to determine a conclusion, to a degree that would be impractical or impossible for a human to do alone in the clinical practice. This could allow for significantly more individualized treatments for each patient. As more data becomes available, it can be fed into the algorithm, which allows it to change based on the new data. However, we must be aware that most studies performed today are still early retrospective studies, and their utility still needs to be evaluated in future large scale prospective studies. Apart from the medical challenges, it must be noted that the impact of large-scale implementation of artificial intelligence will have challenges related to ethical and financial aspects as well.
人工智能（AI）并不是一个新的理念或研究领域。然而，近年来计算技术的进步以及在各个领域应用人工智能经验的不断增加，使我们有希望将其应用于医疗实践，以改善结果。本文旨在评估人工智能（AI）在胃肠病学临床实践中的潜在应用。AI 算法可以提供许多传统诊断、预后、治疗评分或我们今天使用的非 AI 增强程序所没有的优势。它可以非常轻松地处理复杂的数学数据，这将允许考虑许多参数，并使用高度复杂的公式来确定结论，在某种程度上，这对于人类在临床实践中独自完成来说是不切实际或不可能的。这可以为每个患者提供更个性化的治疗。随着更多的数据可用，它可以被输入到算法中，这允许它根据新数据进行更改。然而，我们必须意识到，今天进行的大多数研究仍然是早期的回顾性研究，它们的实用性仍需要在未来的大规模前瞻性研究中进行评估。除了医疗方面的挑战外，还必须指出，人工智能的大规模实施将对伦理和财务方面产生影响。
