Introduction: A diet high in fermented, oligio-, di-, monosaccharide, and polyols

(FODMAP) has been shown to exacerbate symptoms of irritable bowel syndrome

(IBS). Previous literature has shown significant improvement in IBS symptoms after

adherence to a low FODMAP diet (LFD). However, dietary adherence to the LFD is

difficult with patients stating that information provided by healthcare providers

(HCPs) is generalized and nonspecific requiring them to search for supplementary

information to fit their needs. Notably, studies that have used a combination of

online and in-person methods for treatment have shown improved adherence to the

LFD. Objective: To determine whether a novel artificial intelligence (AI) dietary

mobile application will improve adherence to the LFD compared to a standard online

dietary intervention (CON) in populations with IBS or IBS-like symptoms over a 4-

week period. Methods: Participants were randomized into two groups: APP or CON.

The intervention group was provided access to an AI mobile application, a dietary

resource verified by registered dietitians which uses artificial intelligence to

individualize dietary guidance in real-time with the ability to scan menus and

barcodes and provide individuals with food scores based on their dietary preferences.

Primary measures included mobile app engagement, dietary adherence, and

manifestation of IBS-like symptoms. Baseline Results: A total of 58 participants

were randomized to groups. This is an ongoing study and this thesis details the

methodology and baseline characteristics of the participants at baseline and

intervention start. Validation of the application could improve the range of offerings

for lifestyle diseases treatable through dietary modification.