Integrate multi-omics data, single-cell technologies,

The gap

Evidence profile

Sourced from the future work and stated research gap of the source papers, classified as general, spanning 3 journals. Those papers have been cited 11 times in total.

Supporting evidence — 3 representative gaps

• Novel Biomarkers and Use of Artificial Intelligence for Assessing the Risk of Cardiovascular Disease in Individuals with Thyroid Dysfunction: Non-High-Density Lipoprotein Cholesterol Versus Non-High-Density Lipoprotein Cholesterol/High-Density Lipoprotein Cholesterol Ratio (2026) · Journal of Cardiac Critical Care TSS · doi

  Use of AI with novel biomarkers Recent advances in AI have opened new avenues for identifying and integrating novel biomarkers to refine cardiovascular risk prediction in individuals with thyroid dysfunction Beyond traditional lipid indices such as non- HDL cholesterol and NHHR, Al-driven models now incorporate multidimensional data-including inflammatory markers (e.g., hs-CRP, IL-6), oxidative stress indicators, metabolomic signatures and genetic profiles to uncover subtle, non-linear associations between thyroid hormone imbalance and cardiovascular pathology. Machine learning algorithms, particularly deep learning and ensemble methods can analyze large-scale datasets to detect early patterns of endothelia dysfunction, subclinical atherosclerosis, and cardiometabolic derangements that may not be apparent through conventional statistical approaches. Emerging studies up to 2026 suggest that Al-assisted biomarker panels significantly enhance risk stratification by enabling personalized prediction models, thereby facilitating earlier intervention and targeted therapeutic strategies in this high-risk population. Importantly, such approaches also allow dynamic risk assessment by continuously integrating longitudinal patient data, marking a shift from static to adaptive cardiovascular risk evaluation in thyroid disorders CONCLUSION lipid profile markers and All atherogenic indices examined showed a significant correlation with thyroid hormones in individuals with thyroid dysfunction. Both non-HDL-C and NHHR are important biomarkers for individuals who have thyroid dysfunction. assessing However, the NHHR outperformed traditional lipid parameters and other atherogenic indices, making it a more sensitive indicator of dyslipidemia and CVD risk assessment. The study emphasized the importance of monitoring lipid levels with atherogenic indices to prevent or reduce the incidence of CVD in individuals with thyroid dysfunction. Ethical approval: The research/study was approved by the Institutional Review Board at Afe Babalola University Multi- System Hospital (AMSH), number AMSH/REC/25/55/116, dated 28th August 2025. Declaration of patient consent: The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understand that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed. Financial support and sponsorship: Nil. Conflicts of interest: There are no conflicts of interest.

  generalfuture workevidence 5/5
  Keywords: thyroid risk patient dysfunction individuals lipid indices biomarkers cardiovascular nhhr atherogenic consent novel integrating prediction
• A novel clinical perspective on subarachnoid hemorrhage complicated by myocardial injury: independent predictors and short-term prognostic assessment (2026) · Frontiers in Neurology · doi

  Future research should prioritize multicenter prospective studies with larger sample sizes and independent external validation cohorts to assess the stability, calibration, and transportability of the proposed models. Prospective impact studies are also needed to determine whether nomogram-guided risk stratification improves clinical decision-making or patient outcomes. Advanced imaging techniques, such as cardiac magnetic resonance imaging (CMR), together with dynamic cardiac biomarkers and hemodynamic parameters, may further clarify the clinical significance of non-coronary myocardial injury after SAH. With advances in artificial intelligence and machine learning, multidimensional data-fusion models may eventually support precision risk assessment, but such tools should undergo clinical implementation.

  generalfuture workevidence 5/5
  Keywords: clinical prospective external validation models risk imaging cardiac future prioritize multicenter larger sample sizes independent
• Molecular mechanisms and therapeutic progress in atherosclerosis: bridging immune inflammation and precision medicine (2026) · Frontiers in Immunology · cited 11× · doi

  There is a need to integrate multi-omics data, single-cell technologies, and artificial intelligence for advancing precision medicine in atherosclerosis. Current therapeutic strategies have limitations, and new approaches are needed to target specific molecular pathways and immune-inflammatory networks. The paper identifies a gap in the development of individualized risk prediction models and targeted interventions.

  generalstated research gapevidence 5/5
  Keywords: there need integrate multi-omics data single-cell technologies artificial

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