ReviewBioengineered2023
Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae.
Review in Bioengineered, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed.
- Flavonoids: biological activities, nutritional and immunological aspects, therapeutic potential, food applications, and human health benefits-A comprehensive review.Frontiers in nutrition · 2026Review
- Influence of Light Regimes on Production of Beneficial Pigments and Nutrients by Microalgae for Functional Plant-Based Foods.Foods (Basel, Switzerland) · 2025Review
- Artificial Intelligence in Advancing Algal Bioactive Ingredients: Production, Characterization, and Application.Foods (Basel, Switzerland) · 2025Review
- Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses.Bioengineering (Basel, Switzerland) · 2024Review
- Microalgae Flocculation: Assessment of Extraction Yields and Biological Activity.International journal of molecular sciences · 2024Article
- Bioactivity and Bioavailability of Carotenoids Applied in Human Health: Technological Advances and Innovation.International journal of molecular sciences · 2024Review
- Microalgae biofuels: illuminating the path to a sustainable future amidst challenges and opportunities.Biotechnology for biofuels and bioproducts · 2024Review
- Machine learning-based prediction models unleash the enhanced production of fucoxanthin inFrontiers in plant science · 2024Article
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
No grant is acknowledged in the PubMed record.
Abstract
Fucoxanthin is a carotenoid that possesses various beneficial medicinal properties for human well-being. However, the current extraction technologies and quantification techniques are still lacking in terms of cost validation, high energy consumption, long extraction time, and low yield production. To date, artificial intelligence (AI) models can assist and improvise the bottleneck of fucoxanthin extraction and quantification process by establishing new technologies and processes which involve big data, digitalization, and automation for efficiency fucoxanthin production. This review highlights the application of AI models such as artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS), capable of learning patterns and relationships from large datasets, capturing non-linearity, and predicting optimal conditions that significantly impact the fucoxanthin extraction yield. On top of that, combining metaheuristic algorithm such as genetic algorithm (GA) can further improve the parameter space and discovery of optimal conditions of ANN and ANFIS models, which results in high R
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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.