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Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Several recent Canadian population-based studies have shown that many patients at high CVD risk continue to have low-density lipoprotein cholesterol (LDL-C) levels well above the guideline targets [2,3]. LDL-C has been extensively studied and described as a causal factor for CVD [4]. LDL-C levels above the target can result from multiple factors such as insufficient LDL-C lowering with statins, statin-related side effects, suboptimal medication adherence, and treatment inertia [5].

Meaghan E Kavanagh, Laura Chiavaroli, Selina M Quibrantar, Gabrielle Viscardi, Kimberly Ramboanga, Natalie Amlin, Melanie Paquette, Sandhya Sahye-Pudaruth, Darshna Patel, Shannan M Grant, Andrea J Glenn, Sabrina Ayoub-Charette, Andreea Zurbau, Robert G Josse, Vasanti S Malik, Cyril W C Kendall, David J A Jenkins, John L Sievenpiper

JMIR Cardio 2025;9:e58124

Applications of AI in Predicting Drug Responses for Type 2 Diabetes

Applications of AI in Predicting Drug Responses for Type 2 Diabetes

The studies were first filtered for “type 2 diabetes” and then for other disease areas such as arthritis, multiple sclerosis, and cardiovascular diseases (Figure 1 A-C). These additional conditions were chosen because they are widely studied in relation to drug response and represent areas where AI methods have shown emerging applications.

Shilpa Garg, Robert Kitchen, Ramneek Gupta, Ewan Pearson

JMIR Diabetes 2025;10:e66831