biostudies-literatureUnknown26Chan PZ<h4>Background</h4>Current blood glucose monitoring (BGM) methods are often invasive and require repetitive pricking of a finger to obtain blood samples, predisposing individuals to pain, discomfort, and infection. Noninvasive blood glucose monitoring (NIBGM) is ideal for minimizing discomfort, reducing the risk of infection, and increasing convenience.<h4>Objective</h4>This review aimed to map the use cases of artificial intelligence (AI) in NIBGM.<h4>Methods</h4>A systematic scoping review was conducted according to the Arksey O'Malley five-step framework. Eight electronic databases (CINAHL, Embase, PubMed, Web of Science, Scopus, The Cochrane-Central Library, ACM Digital Library, and IEEE Xplore) were searched from inception until February 8, 2023. Study selection was conducted by 2 indJournal of medical Internet researche58892https://www.ebi.ac.uk/biostudies/studies/S-EPMC11615544biostudies-literatureAI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.PMC11615544Jin EChan PZChew HSJJansson MfalseAI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.<h4>Background</h4>Current blood glucose monitoring (BGM) methods are often invasive and require repetitive pricking of a finger to obtain blood samples, predisposing individuals to pain, discomfort, and infection. Noninvasive blood glucose monitoring (NIBGM) is ideal for minimizing discomfort, reducing the risk of infection, and increasing convenience.<h4>Objective</h4>This review aimed to map the use cases of artificial intelligence (AI) in NIBGM.<h4>Methods</h4>A systematic scoping review was conducted according to the Arksey O'Malley five-step framework. Eight electronic databases (CINAHL, Embase, PubMed, Web of Science, Scopus, The Cochrane-Central Library, ACM Digital Library, and IEEE Xplore) were searched from inception until February 8, 2023. Study selection was conducted by 2 ind2024-01-01T00:00:00Z2024 Nov2025-04-27T02:15:58.141Z2025-04-06T18:32:04.094ZS-EPMC116155443956135310.2196/58892