BACKGROUND: Limited federal premarket oversight over US-sold dietary supplements impedes consumer safety and product efficacy. The Dietary Supplement Label Database (DSLD) was created to increase publicly available information on US-sold dietary supplements. Building on what the DSLD was designed to provide, we aimed to create a comprehensive database that can facilitate searches on supplements sold with weight-loss, muscle-building, and cleanse/detox claims, supplement categories previously flagged for misleading claims and containing toxic ingredients. OBJECTIVE: Leverage publicly available DSLD API to develop an easy-to-use tool to classify DSLD supplement labels with weight-loss, muscle-building, and cleanse/detox claims. METHODS: A four-step categorization methodology was used to develop the tool: (1) Create reference standard database by deductively coding claims (weight-loss, muscle-building, cleanse/detox) on 5000 DSLD labels. (2) Develop three systematic heuristics (one per claim) and refine heuristics as assessed by recall, specificity, precision, negative predictive value, F1 Score, and accuracy. (3) Develop multimodal deep learning model as additional method to identify the three claims. (4) Compare models' performance using ROC curve and efficiency analyses (i.e., hours of human labor taken to develop each model). RESULTS: Of the 4745 DSLD labels included in the reference standard database, 4.2% were defined using the criteria as weight-loss, 6.3% muscle-building, and 3.0% cleanse/detox. Three systematic heuristics for each claim were refined four times, with pass four exceeding prior passes' performances. ROC curve analyses indicated systematic heuristic performed significantly better (P<
0.05) than multimodal deep learning model at classifying cleanse/detox labels, yet efficiency analyses found systematic heuristics less efficient (110 versus 30 hours). CONCLUSION: Our findings illustrate the feasibility of using the DSLD API to create a tool that classifies weight-loss, muscle-building, and cleanse/detox labels using our supplement label categorization methodology. This publicly available tool, STRIPED Dietary Supplement Label Explorer, may be used to support future research and the monitoring of claims on dietary supplement labels.