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- 0040 Machine learning algorithms as tools for identifying predictive autoantibody biomarkers in pemphigus vulgaris
- Integrating Biomarkers from Correlation Analysis and Metric Learning for Hair Loss Classification
- Non-invasive Approaches for the Diagnosis of Autoimmune/Autoinflammatory Skin Diseases—A Focus on Psoriasis and Lupus erythematosus
- Skin deep: dermatologic challenges in PCOS through the female lifespan
- QuantAnts machines discover biomarkers for RAS signaling activation and design sgRNAs for CRISPR to target complex CD9, CD34, and CD74.
- 1616 Cross-comparison of inflammatory skin disease transcriptomics identifies PTEN as a pathogenic disease classifier in cutaneous lupus erythematosus
- Use of Single‐Cell Data and scPagwas Analysis to Identify T Cell Subsets and Construct a Prognostic Model for Clear Cell Renal Cell Carcinoma
- CD27 and IL-35 as diagnostic biomarkers in alopecia areata: First evidence of association with pathogenic scalp bacterial infections
- Repurposing FDA approved drugs for psoriasis indications through integrated molecular docking, one-SVM algorithm, and molecular dynamics simulation approaches
- A consensus-based treatment algorithm for alopecia areata in adolescents and adults: integrating severity, quality of life, and disease dynamics
- A Feature-Preserving Hair Removal Algorithm for Dermoscopy Images
- Comparative investigation of immune-related biomarkers related to alopecia areata subtypes
- Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms
- Metabolic syndrome and the skin: a more than superficial association. Reviewing the association between skin diseases and metabolic syndrome and a clinical decision algorithm for high risk patients
- PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
- A systematic simulation-based meta-analytical framework for prediction of physiological biomarkers in alopecia
- Biomarker-based methods for determining noncompliance in a prevention trial
- Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods
- Long-lived proteins and DNA as candidate predictive biomarkers for tissue associated diseases
- Human Hair as a Testing Substrate in the Era of Precision Medicine: Potential Role of ‘Omics-Based Approaches
- JAK-centric explainable few-shot gene-expression diagnosis framework for alopecia via MultiPLIER priors and relation-style set-to-set comparison
- A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach
- Comparative Characterization of Human Meibomian Glands, Free Sebaceous Glands, and Hair-Associated Sebaceous Glands Based on Biomarkers, Analysis of Secretion Composition, and Gland Morphology
- Long COVID syndrome: An unfolding enigma
- The role of multiomics in revealing the mechanism of skin repair and regeneration
- Unveiling Post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population
- Scalp Bacterial Microbiota Dysbiosis in Androgenetic Alopecia: Community Structure, Functional Profiles, and Associations with Lifestyle Factors
- Xgboost Algoritmasıyla Polikistik Over Sendromu Teşhisi
- Causal associations between plasma proteins and prostate cancer: a Proteome-Wide Mendelian Randomization
- Peripheral blood gene expression in alopecia areata reveals molecular pathways distinguishing heritability, disease and severity