Overcoming barriers to implementation of artificial intelligence in gastroenterology

Artificial intelligence is poised to revolutionize the field of medicine, however significant questions must be answered prior to its implementation on a regular basis. Many artificial intelligence algorithms remain limited by isolated datasets which may cause selection bias and truncated learning for the program. While a central database may solve this issue, several barriers such as security, patient consent, and management structure prevent this from being implemented. An additional barrier to daily use is device approval by the Food and Drug Administration. In order for this to occur, clinical studies must address new endpoints, including and beyond the traditional bio- and medical statistics. These must showcase artificial intelligence's benefit and answer key questions, including challenges posed in the field of medical ethics.