Kerr David, Klonoff David C
1 Sansum Diabetes Research Institute, Santa Barbara, CA, USA.
2 Mills-Peninsula Medical Center, San Mateo, CA, USA.
J Diabetes Sci Technol. 2019 Jan;13(1):123-127. doi: 10.1177/1932296818796508. Epub 2018 Sep 5.
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on personal phenotypic and genotypic information will lead to selections of tailored, effective therapies that will transform health care. However, decision-making processes based exclusively on quantitative metrics that ignore qualitative factors could create a quantitative fallacy. Difficult to quantify inputs into AI-based therapeutic decision-making processes include empathy, compassion, experience, and unconscious bias. Failure to consider these "softer" variables could lead to important errors. In other words, that which is not quantified about human health and behavior is still part of the calculus for determining therapeutic interventions.
未来,人工智能(AI)有潜力改善糖尿病护理的效果。随着用于生理监测的新型传感器的出现以及智能胰岛素笔的引入,基于个人表型和基因型信息的新型数据关系将带来量身定制的有效治疗方案的选择,这将改变医疗保健。然而,仅基于忽视定性因素的定量指标的决策过程可能会产生定量谬误。难以量化输入基于人工智能的治疗决策过程的因素包括同理心、同情心、经验和无意识偏见。不考虑这些“较软”变量可能会导致重大错误。换句话说,人类健康和行为中未被量化的部分仍然是确定治疗干预措施的计算的一部分。