ArticleFoods (Basel, Switzerland)2025
Multi-Scale Feature Attention Network for Rapid and Non-Destructive Quantification of Aflatoxin B
Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Advances in Machine Learning and Deep Learning Algorithm-Assisted Hyperspectral Imaging for Food Quality and Safety Assessment.Foods (Basel, Switzerland) · 2026Review
- Detection of Frost-Damaged Maize Kernels for Food Quality Screening Using Hyperspectral Imaging and 2D-COS-Assisted Deep Learning.Food science & nutrition · 2026Article
- A Blockchain-Based Dual-Track Mechanism for Trusted Circulation of Food Safety Detection Data and Batch-Level Risk Control: An Aflatoxin B1 Case Study.Foods (Basel, Switzerland) · 2026Article
- A Preliminary Food-AI Readiness Framework for AI-Enabled Hyperspectral Systems in Fungal and Mycotoxin Risk Management: A Critical Narrative Review.Foods (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Maize, a globally important crop, is highly susceptible to aflatoxin contamination, posing a serious threat. Therefore, accurate detection of aflatoxin levels in maize is of critical importance. In this study, the Multi-Scale Feature Network with Efficient Channel Attention (MSFNet-ECA) model, based on near-infrared hyperspectral imaging combined with deep learning techniques was developed to analyze the content of aflatoxin B
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.