Notas clínicas
Notas ancladas en evidencia sobre exactitud de la evaluación dietética, reconocimiento de alimentos por IA, estándares de validación y cómo elegir una app de salud. Cada nota cita fuentes revisadas por pares con DOI cuando las afirmaciones lo requieren.
Nutrola vs PlateLens (2026): Auditable Provenance vs an Unlocatable Benchmark
Nutrola's food data is auditable (USDA FoodData Central, OpenFoodFacts) and its methodology documented, though independent validation is pending (Evidence Grade C). PlateLens's ±1.1% MAPE cites benchmarks with no locatable public record. A clinical, evidence-graded comparison.
How Accurate Are Calorie Tracking Apps in 2026? A Clinical Review of the Evidence
Consumer calorie tracker outputs typically carry a ±15–25% MAPE per meal — adequate for general weight management, below clinical-grade dietary assessment. A review of validation evidence and error sources.
How to Choose a Calorie Tracking App: A Decision Framework
A question-driven framework for choosing a consumer calorie tracker — picking by use case (weight management, recomposition, clinical), paradigm (photo-AI vs search), evidence requirement, and budget.
How We Evidence-Grade Consumer Health Apps (A–F)
Clinical App Report assigns an Evidence Grade A–F to every evaluated consumer health application based on the published validation evidence. A explainer of the grading rubric, examples, and why most consumer apps land in Grade C–D.