Evidence map›Paper›PMID 41901927›Full record

ArticleSensors (Basel, Switzerland)2026

Machine Learning-Driven Computer Vision System for Automated Fat and Energy Quantification in Human Milk Microcapillaries.

Lujan E Huamanga-Chumbes, Erwin J Sacoto-Cabrera, Jaime Lloret, Vinie Lee Silva-Alvarado, Alfz Huicho-Mendigure, Edison Moreno-Cardenas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lujan E Huamanga-ChumbesTESLA Laboratory, Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Cusco 08003, Peru.ORCID 0009-0008-7142-7577
Erwin J Sacoto-CabreraGIHP4C, Universidad Politécnica Salesiana, Cuenca 010102, Ecuador.ORCID 0000-0003-2916-0369
Jaime LloretInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, Carrer del Paranimf 1, Grao de Gandia, 46730 Valencia, Spain.ORCID 0000-0002-0862-0533
Vinie Lee Silva-AlvaradoInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, Carrer del Paranimf 1, Grao de Gandia, 46730 Valencia, Spain.ORCID 0009-0000-5857-3248
Alfz Huicho-MendigureTESLA Laboratory, Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Cusco 08003, Peru.ORCID 0000-0001-5421-7342
Edison Moreno-CardenasTESLA Laboratory, Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Cusco 08003, Peru.ORCID 0000-0001-9545-4694

Funding

National University of San Antonio Abad of Cusco Projects of the Professional School of Electronic EngineeringUniversidad Politécnica Salesiana Fog Computing Simulation projectUniversitat Politècnica de València Programa de Ayudas de Investigación y Desarrollo (PAID-01-24)
6 · The paper itself

Abstract

Neonatal health requires precise lipid quantification in human milk to ensure proper nutritional development. Traditional manual methods, such as the creamatocrit, are limited by human-induced bias and significant measurement uncertainty. This study presents a low-cost Computer Vision System acting as an automated optical sensing modality for estimate the cream fraction (

Indexed as

LipidsMachine LearningMilk, HumanHumansLipidsclinical informaticscomputer vision systemhuman milkimage segmentationmachine learningneonatal nutritionuncertainty analysis

Identifiers

PMID41901927
PMCPMC13030702

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.