ReviewInternational journal of molecular sciences2022
Addressing the Clinical Feasibility of Adopting Circulating miRNA for Breast Cancer Detection, Monitoring and Management with Artificial Intelligence and Machine Learning Platforms.
Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 23 citations in OpenAlex.
- Circulating miRNAs for glioblastoma monitoring: from biofluid to clinical decision.Molecular therapy. Oncology · 2026Review
- Artificial intelligence-based miRNA analysis for precision oncology: diagnostic and prognostic insights.Frontiers in molecular biosciences · 2026Review
- Exosomal miRNA-based theranostics in cervical cancer: bridging diagnostics and therapy.Medical oncology (Northwood, London, England) · 2025Review
- Artificial intelligence utilization in cancer screening program across ASEAN: a scoping review.BMC cancer · 2025Article
- Electrochemical Biosensors for the Detection of Exosomal microRNA Biomarkers for Early Diagnosis of Neurodegenerative Diseases.Analytical chemistry · 2025Review
- Liquid biopsy using non-coding RNAs and extracellular vesicles for breast cancer management.Breast cancer (Tokyo, Japan) · 2025Review
- Recent Advancements in Breast Cancer Therapies and Biomarkers: Mechanisms and Clinical Significance.Current pharmaceutical biotechnology · 2025Review
- An Integrated Care Approach to Improve Well-Being in Breast Cancer Patients.Current oncology reports · 2024Review
- The increasing importance of novel deep eutectic solvents as potential effective antimicrobials and other medicinal properties.World journal of microbiology & biotechnology · 2023Review
- The Role of MicroRNAs in Breast Cancer and the Challenges of Their Clinical Application.Diagnostics (Basel, Switzerland) · 2023Review
- Microfluidics for Profiling miRNA Biomarker Panels in AI-Assisted Cancer Diagnosis and Prognosis.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
Abstract
Detecting breast cancer (BC) at the initial stages of progression has always been regarded as a lifesaving intervention. With modern technology, extensive studies have unraveled the complexity of BC, but the current standard practice of early breast cancer screening and clinical management of cancer progression is still heavily dependent on tissue biopsies, which are invasive and limited in capturing definitive cancer signatures for more comprehensive applications to improve outcomes in BC care and treatments. In recent years, reviews and studies have shown that liquid biopsies in the form of blood, containing free circulating and exosomal microRNAs (miRNAs), have become increasingly evident as a potential minimally invasive alternative to tissue biopsy or as a complement to biomarkers in assessing and classifying BC. As such, in this review, the potential of miRNAs as the key BC signatures in liquid biopsy are addressed, including the role of artificial intelligence (AI) and machine learning platforms (ML), in capitalizing on the big data of miRNA for a more comprehensive assessment of the cancer, leading to practical clinical utility in BC management.
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.