Lars Henriksen, PhD
Methods Lead, Epidemiology
Lars Henriksen leads the Initiative's epidemiologic methods strand, with a focus on bias structures in self-reported and AI-mediated dietary intake data and on systematic-review methodology for digital health applications. PhD in Epidemiology; prior faculty appointments in nutritional epidemiology.
Areas of work: Systematic review methodology; Measurement error; Self-report bias; Digital health epidemiology
Joined the Initiative: 2023-09
ORCID: 0000-0002-2051-7733
Publications
- Independent validation of six commercial AI-assisted dietary assessment applications against weighed-food reference: a 180-meal cross-sectional study (2026)
- Photo-based vs. manual-entry dietary assessment: a meta-analysis of accuracy differentials (2026)
- What level of dietary assessment accuracy supports patient self-monitoring? A position paper (2026)
- Independent validation of image-based dietary assessment applications: a systematic review and meta-analysis (2018-2024) (2025)
- Equivalence testing in nutritional epidemiology: when 'no significant difference' is not enough (2025)
- Cuisine and population coverage in image-based dietary assessment benchmarks: an analysis of 23 published evaluation sets (2025)
- Vendor-reported accuracy claims for image-based dietary assessment applications: a systematic review of methodology gaps (2024)
- Bland-Altman analysis for dietary assessment validation: conventions, common errors, and recommended reporting (2024)
Preprints
Methodology briefs
- Pre-specifying equivalence margins for dietary assessment non-inferiority claims (2026)
- Labelling vendor-reported vs. independently-replicated accuracy numbers: an editorial convention (2025)
Commentary
- Have AI nutrition coaching claims gotten ahead of the validation evidence? (2026)
- Comments on the 2025 ICMJE disclosure update and what it means for digital health validation (2025)
- Why most vendor-reported accuracy numbers fail to replicate, and what 'fail' really means (2024)
- PubMed search strategies for finding image-based dietary assessment validation studies (2024)