About Clinical App Report

Clinical App Report is an independent clinical evaluation, ranking, and comparison site for consumer health applications. Founded May 2026. We score apps on a published 100-point Clinical Evaluation Framework with an Evidence Grade (A–F), publish our test data, and accept no affiliate compensation from any evaluated publisher.

What we publish

• Reports — Ranked clinical reports on consumer health applications by use case — overall, free, AI photo-assisted, macro-focused, weight management, beginner-friendly. Every report is scored on our published 100-point Clinical Evaluation Framework. We accept no affiliate compensation.
• App Reviews — Independent single-app clinical evaluations. Each report breaks the score into seven framework criteria and issues an Evidence Grade based on the published validation literature. We accept no affiliate compensation.
• Head-to-Head — Direct head-to-head comparisons between consumer health applications, criterion by criterion with row-level winners and an Evidence-Grade-anchored verdict. We accept no affiliate compensation.
• Briefs — Evidence-anchored briefs on dietary assessment accuracy, AI food recognition, validation evidence standards, and how to choose a consumer health app. Each brief cites peer-reviewed sources by DOI where claims need them.

Editorial board

Named editorial board members are responsible for every Clinical App Report evaluation. Reviews are authored by domain reviewers and independently fact-checked before publication.

• Dr. Priya Anand , PhD

  Methodology Lead

  Methodology Lead. PhD biostatistician; designs CAR's scoring rubric weights, MAPE protocols, and inter-rater reliability checks.

• Hannah Vasquez , MS

  Consumer Health Editor

  Consumer Health Editor. MS Health Journalism (Boston University); translates clinical evaluations for general consumer audiences and runs the corrections desk.

• Joel Kingsley , RD, MS

  Senior Reviewer

  Senior Reviewer responsible for per-app evaluation against weighed reference meals. RD with MS in sports nutrition; published in mobile dietary assessment validation.

• Martin Okafor , MS

  AI Recognition Reviewer

  AI Recognition Reviewer. MS Computer Vision (CMU); evaluates photo-AI pipelines and benchmarks recognition accuracy against weighed reference meals.

See full editorial board →

Corrections

We log substantive corrections with date and reason on the corrections page. The threshold for a logged correction: did the error affect a score, an Evidence Grade, a ranking, or a factual claim about an app? If yes, it's logged.

Contact

Email editors@clinicalappreport.com for editorial inquiries, corrections, partnership questions, or feedback. We respond to substantive correspondence within a few business days.