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This thesis presents research conducted in partial fulfillment of a Master's degree in Software Systems Engineering but does not report new empirical findings.

This study identified 12 potential candidate biomarkers associated with hair loss by analyzing the differential expression of genes, suggesting possible therapeutic targets for alopecia.

This review systematically analyzed 22 clinical trials on hair care, finding that while most studies employed appropriate statistical methods, significant inconsistencies in reporting test assumptions and effect sizes may hinder reproducibility, highlighting a need for better standardization and transparency in these research practices.

This study performed a bibliometric analysis on Alzheimer's disease and white matter research from 1981 to 2023, finding the majority of publications from the US, China, and the UK, with key themes like mild cognitive impairment and MRI appearing frequently.

This study outlines the Human Gene Correlation Analysis tool, which classifies human genes by coexpression levels and identifies overrepresented annotation terms in correlated gene groups, with no new clinical results reported.

This study developed a deep-learning model that accurately diagnosed alopecia areata with an accuracy of 88.92% and distinguished its activity levels with an accuracy of 83.33%, highlighting the potential for artificial intelligence in improving the diagnosis and treatment of this autoimmune hair loss condition.

This study suggests that estimating autism likelihood as early as one month after birth may enable more precise early intervention for children with developmental support needs, potentially improving diagnosis, workflows, and reducing service wait times.

The BAYONET trial is a phase II study designed to assess the efficacy and safety of combining encorafenib, binimetinib, and cetuximab for patients with BRAF V600E-mutant metastatic colorectal cancer that is resistant to encorafenib plus cetuximab; results are not yet reported.

This study introduced Neurospectrum, a framework that effectively identifies meaningful neural dynamics by encoding neural activity into latent trajectories, and reported that it outperformed traditional methods in tracking synchronization, reconstructing stimuli, and identifying fMRI biomarkers in various datasets.

This study found a causal link between eight blood metabolites and allergic conjunctivitis, highlighting their potential role in predicting and preventing the condition.

This review assesses existing knowledge about the 17q21.31 inversion polymorphism, highlighting its genetic structure differences across ancestries, associations with various diseases, and implications for precision medicine and drug discovery.

This research explores the pathogenesis of benign prostatic hyperplasia and evaluates the combined effect of finasteride and anastrozole in treating BPH in a rat model, but reports no new results yet.

This study found that Cochrane systematic reviews on drug safety had higher methodological quality than non-Cochrane reviews, with the type of review and disease area affecting quality.

This study introduces an extended approach to the Bonferroni procedure that accounts for correlations among endpoints, aiming to improve test power while maintaining strong control of the family-wise type I error rate in clinical trials.

This study identified three new genetic loci associated with PCOS and found a similar genetic structure across different diagnostic criteria, suggesting a genetic basis for shared metabolic traits and potential causal links to other conditions.

Some human genetic markers work for genetic studies in pig-tailed and stump-tailed macaques, which can help in their conservation.

This study introduced a novel framework that significantly improves the accuracy of alopecia areata lesion segmentation in semi-supervised scenarios, outperforming existing methods and aiding in the disease's diagnosis, treatment, and staging, which can impact quality of life and mental well-being.

In this study, the researchers performed a comparative analysis of drug-target interaction data from multiple databases to refine drug repurposing strategies, revealing potential associations between drug characteristics and therapeutic groups, and predicting repositioning opportunities for FDA-approved drugs across major cancer types.

This narrative review discusses various epidemiological study designs, the importance of reliable bias assessment tools, and the implications of database use for hypothesis testing in different research areas; it reports no new results.

This study found that self-monitoring blood pressure among pregnant women with hypertension did not significantly improve clinical outcomes compared to usual care, though women reported positive cognitive and emotional responses.

This study found that current automatic text generation metrics do not predict human preference judgments for long-form question answering, and suggests adopting a multi-faceted evaluation approach focusing on aspects like factuality and completeness.

This study suggests that genetic overlap between alopecia areata and major depressive disorder may be limited to the MHC region, highlighting the need for further research.

This study introduces a novel computational model using fuzzy logic and multi-criteria decision-making techniques to create a triage system for androgenetic alopecia management, stratifying patients into seven severity levels and aiding in resource allocation and treatment planning.

This article describes how PESCADOR software assists in creating detailed biological pathway charts from PubMed abstracts, focusing on hair and breast development case studies without providing new clinical results.

This editorial for the Journal of Evidence-Based Medicine reports no new results.

This table reports gene set enrichment analysis scores for hair follicle compartments across diseases and sampling methods, providing comparisons but no new experimental findings.

This study examined the genetic basis of alopecia areata by analyzing gene expression differences between patients and healthy controls, identifying critical pathways, hub genes, transcription factors, and miRNAs implicated in the disease, and suggesting potential targets for treatment.