ReviewBiomolecules2021
Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.
Review in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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.
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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.
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Who cites it
19 citing papers in PubMed, 28 citations in OpenAlex.
- MASLD biomarker discovery: evaluating lipidomics techniques across disease progression.Molecular biology reports · 2026Review
- The MALDI Method to Analyze the Lipid Profile, Including Cholesterol, Triglycerides and Other Lipids.Current issues in molecular biology · 2026Review
- Serum lipidome remodeling in viral pneumonia: from pathophysiology to therapeutics.Frontiers in immunology · 2026Review
- Circulating Lipid Profiles Indicate Incomplete Metabolic Recovery After Weight Loss, Suggesting the Need for Additional Interventions in Severe Obesity.Biomolecules · 2025Article
- Combining lipidomics and machine learning to identify lipid biomarkers for nonsyndromic cleft lip with palate.JCI insight · 2025Article
- Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes.World journal of gastroenterology · 2025Article
- Multi-omics profiling reveals altered mitochondrial metabolism in adipose tissue from patients with metabolic dysfunction-associated steatohepatitis.EBioMedicine · 2025Observational
- The role of artificial intelligence in the management of liver diseases.The Kaohsiung journal of medical sciences · 2024Review
- Lipidomic Analysis Reveals Branched-Chain and Cyclic Fatty Acids fromMolecules (Basel, Switzerland) · 2024Article
- Effects of Combined Low-Dose Spironolactone Plus Vitamin E versus Vitamin E Monotherapy on Lipidomic Profile in Non-Alcoholic Fatty Liver Disease: A Post Hoc Analysis of a Randomized Controlled Trial.Journal of clinical medicine · 2024Article
- Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach.International journal of molecular sciences · 2024Article
- Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD.Nature communications · 2024Article
- Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression.Clinical and molecular hepatology · 2024Article
- Rise of Deep Learning Clinical Applications and Challenges in Omics Data: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Combining Semi-Targeted Metabolomics and Machine Learning to Identify Metabolic Alterations in the Serum and Urine of Hospitalized Patients with COVID-19.Biomolecules · 2023Article
- Measurement of lipid flux to advance translational research: evolution of classic methods to the future of precision health.Experimental & molecular medicine · 2022Review
- Metabolomics in Bariatric and Metabolic Surgery Research and the Potential of Deep Learning in Bridging the Gap.Metabolites · 2022Article
- Afamin Levels and Their Correlation with Oxidative and Lipid Parameters in Non-diabetic, Obese Patients.Biomolecules · 2022Article
- Artificial intelligence applied to omics data in liver diseases: Enhancing clinical predictions.Frontiers in artificial intelligence · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible. Given this complex situation, the search for noninvasive alternatives is clinically important. A hallmark of NAFLD progression is the dysregulation in lipid metabolism. In this context, recent advances in the area of machine learning have increased the interest in evaluating whether multi-omics data analysis performed on peripheral blood can enhance human interpretation. In the present review, we show how the use of machine learning can identify sets of lipids as predictive biomarkers of NAFLD progression. This approach could potentially help clinicians to improve the diagnosis accuracy and predict the future risk of the disease. While NAFLD has no effective treatment yet, the key to slowing the progression of the disease may lie in predictive robust biomarkers. Hence, to detect this disease as soon as possible, the use of computational science can help us to make a more accurate and reliable diagnosis. We aimed to provide a general overview for all readers interested in implementing these methods.
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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 Socratic graph.