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OBJECTIVE: To assess for feasibility, acceptability, and preliminary effectiveness of an ethnoracially-matched family navigation intervention aimed at reducing barriers to developmental evaluations for preschoolers with developmental concern attending Head Start. METHODS: Fifty-eight parents of Head Start preschoolers who were identified as at risk for developmental delay were assigned using stratified block random sampling to the family navigation intervention (n = 28) and 30 controls (usual care). Key outcomes included the percentage of children who completed the planned intervention visits, satisfaction with the intervention, and the proportion of children guided by family navigators who completed developmental evaluations. RESULTS: Of the 28 families, 21 parents completed the family navigation intervention visits. The intervention sample was diverse, including 57% Black, 24% White, and 19% Latino(a) parents. Ninety percent of Head Start educators (n = 18) and 100% of healthcare providers (n = 6) were satisfied with the intervention. Parents qualitatively reported that they valued the advocacy support from the family navigators and navigators (n = 7) valued their role in "giving back." Sixty-six percent of the intervention group were seen by a healthcare provider to discuss developmental concerns showing preliminary effectiveness for completion of healthcare evaluations. However, there was no significant difference between those in the intervention and control group completing Head Start recommended evaluations, and over half of all participants were not referred for educational evaluations. CONCLUSION: Results support the feasibility, acceptability, and preliminary effectiveness of an ethnoracially matched family navigation intervention to reduce barriers to developmental healthcare evaluations for preschoolers at risk for developmental delays. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03499405; Date of Registration: April 9, 2018.
BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.
BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.
BACKGROUND & OBJECTIVE: Children with Developmental Coordination Disorder (DCD) face significant, yet often overlooked, challenges beyond motor impairments, including difficulties with toilet training and bladder and bowel dysfunctions (BBD). This study aims to explore whether children with DCD exhibit greater difficulties in these areas compared to typically developing children (TDC). METHOD: This cross-sectional case-control study included 84 children aged 5-8 years (42 DCD, 42 TDC), matched by school-grade and sex (33 boys and 9 girls per group). Parents completed the Vancouver Symptom Score for Dysfunctional Elimination Syndrome (VSSDES) to assess BBD symptoms, the Dutch DCD-questionnaire (DCD-Q) to evaluate motor coordination, and additional questions regarding toilet training, elimination diagnosis, and co-occurring conditions. Correlations and exploratory group differences were analysed. RESULTS: Parents of children with DCD reported significantly more toilet training difficulties than parents of controls (p < 0.001), including persistent accidents (47.6% vs. 9.5%), prolonged training (45.2% vs. 4.8%), and difficulties recognizing urination urgency (40.5% vs. 2.4%). The parental report of delayed attainment of bowel and bladder control (p < 0.05) and BBD rates (p < 0.001) was also significantly higher in children with DCD. Exploratory analyses indicated that the prevalence of these outcomes was not significantly different between children with DCD with and without co-occurring ADHD or autism, suggesting a possible primary association with DCD. Additionally, across both children with DCD and TDC, poorer motor skills were associated with more BBD symptoms (r = -0.474, p < 0.001). CONCLUSION: Children with DCD have a higher prevalence of toilet training difficulties and BBD compared to TDC, potentially affecting their psychosocial well-being. Greater awareness is crucial for timely and targeted care. Notably, the study's design, directly comparing children diagnosed with DCD to matched TDC, provides new insights into the prevalence of elimination difficulties in this population.
PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.
BACKGROUND: Surgical management of esophageal atresia/tracheoesophageal fistula (EA/TEF) in extremely low birth weight (ELBW) neonates remains challenging and controversial. This study systematically reviews surgical strategies and outcomes in this population. METHODS: Following PRISMA guidelines, Cochrane, Embase, MEDLINE, Scopus, and Web of Science (2004-2024) were searched in February 2025 for studies on surgical management of ELBW neonates with EA/TEF (PROSPERO CRD42025636228). Fatal chromosomal abnormalities were excluded. Demographics, comorbidities, surgical techniques, and complications were analyzed descriptively. Risk of bias was assessed. RESULTS: Eleven publications (five case reports and six case series) comprising 30 patients (Gross type B/C = 1/29) met the eligibility criteria. Mean gestational age was 28.1 (23-34) weeks, and mean birth weight was 760.4 (422-995) g. Twelve primary repairs (PR) and 18 delayed primary repairs (DPR) were performed, including staged repair (n = 11), lower esophageal banding (n = 4), and other techniques (n = 3). Postoperatively, four anastomotic leaks were managed conservatively, six strictures and one recurrent TEF required endoscopic intervention, three fundoplications and two aortopexies were reported (follow-up: 1-198 months, n = 19). Overall mortality was 30% (PR: 8.3%; DPR: 44.4%). Mortality was 60% among neonates with major congenital heart defects (CHD) and 40% among those with VACTERL association. EA/TEF-related complications contributed to 33.3% of deaths. CONCLUSIONS: Mortality in this cohort remains high, particularly with major CHD, and is largely unrelated to EA/TEF-specific complications. In selected cases, PR appears feasible as an alternative to DPR, although conclusions are limited by the small sample size and heterogeneous studies.
INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.
BACKGROUND: Global developmental delay/intellectual disability (GDD/ID) is among the most common neurodevelopmental disorders, with up to half of cases are attributed to genetic factors. Chromosome microarray (CMA) has traditionally been the primary genetic test for idiopathic GDD/ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) have recently emerged, substantially increasing diagnostic yields in these populations. METHODS: We conducted a comprehensive literature search of PubMed, Scopus, EMBASE, and the Cochrane Library from inception to April 29, 2025. Studies reporting the diagnostic utility of these tests in children with GDD/ID were included and analyzed. RESULTS: A total of 102 studies, comprising 55,752 children, were reviewed. The pooled diagnostic yield of WES was 0.37 (95% CI: 0.33-0.41; I2 = 93%), significantly higher than that of CMA at 0.19 (95% CI: 0.16-0.21; I2 = 95%). Subgroup analyses showed that WES yielded significantly higher diagnostic rates than CMA in both same-sample comparisons (OR = 2.27, 95% CI: 1.08-4.78) and different-sample comparisons (OR = 1.65, 95% CI: 1.15-2.37). Only one study evaluated WGS, reporting a diagnostic yield of 0.27. Meta-regression revealed a significant association between CMA diagnostic yield and the proportion of male participants (p < 0.01), but not with WES. No significant difference in diagnostic utility was observed between isolated GDD/ID and GDD/ID with comorbidities. CONCLUSION: In children with unexplained GDD/ID, WES demonstrates superior diagnostic and clinical utility compared to CMA. Incorporating WES as a first-line investigation in the diagnostic evaluation of GDD/ID may be warranted.
ObjectiveTo evaluate the prevalence, access to care, and health outcomes of orofacial clefts (OFCs) among American Indian and Alaska Native (AI/AN) populations through a systematic review and meta-analysis.DesignSystematic review and meta-analysis performed in accordance with PRISMA 2020 guidelines and registered with PROSPERO (CRD420251035364).SettingUS-based population registries, hospital databases, and institutional or community-level retrospective studies involving AI/AN populations.Patients and ParticipantsAI/AN individuals with OFCs compared with non-Hispanic White patients.InterventionsPrimary cleft lip and palate repair, secondary cleft-related procedures, and multidisciplinary cleft care.Main Outcome Measure(s)Prevalence of OFCs, timing of cleft surgery, discharge disposition, access to specialists, and qualitative determinants of disparities.ResultsEighteen studies including more than 1985 AI/AN patients were identified. Meta-analysis of 5 studies estimated a pooled OFC prevalence of 15 per 10 000 live births (95% confidence interval: 5-49), with substantial heterogeneity (I2 = 99.8%). Individual studies reported significantly higher OFC prevalence in AI/AN populations compared to non-Hispanic Whites (odds ratio range: 1.44-2.68). Geographic maldistribution of craniofacial-trained surgeons, increased odds of nonhome discharge, and delayed cleft palate repair were consistently observed barriers. Qualitative analyses highlighted structural inequities, perceived racism, and lack of culturally responsive care as major contributors to disparities.ConclusionsAI/AN populations face a disproportionately high burden of OFCs alongside structural barriers to timely, culturally competent care. Addressing these disparities requires community-engaged, multidisciplinary interventions that improve geographic access and integrate culturally responsive approaches to care.
BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.
Aneurysmal subarachnoid hemorrhage (aSAH) is associated with significant morbidity and mortality, with cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) being the primary contributors to poor outcomes. Magnesium sulfate (MgSO₄) has demonstrated neuroprotective and vasodilatory properties in preclinical models. This study aimed to evaluate the effect of targeted serum magnesium (Mg) maintenance on CV and exploratory clinical outcomes following aSAH. We conducted a prospective, multicenter, single-blind RCT across four neurocritical care units in Korea between 2019 and 2024. A total of 121 aSAH patients were randomized to receive either IV MgSO₄or placebo within six hours of admission. Mg was infused to maintain serum concentrations between 2.0 and 3.0 mg/dL for 14 days. The primary outcome was incidence of CV assessed by transcranial doppler. Secondary outcomes included DCI, ICU and hospital length of stay, modified rankin scale (mRS) at 30 days. There was no significant difference in overall CV incidence; however, the Mg group demonstrated significantly lower mean flow velocity and Lindegaard ratio on days 4-9, indicating reduced vasospasm severity. In exploratory multivariable analyses, a median serum Mg concentration > 2.5 mg/dL during the first 14 hospital days was independently associated with lower risks of CV and DCI. No significant differences were found in mRS scores, ICU and hospital stay, or serious adverse events between groups. Early targeted Mg administration improved TCD-derived hemodynamic markers during the peak vasospasm window; however, it did not significantly reduce CV incidence, DCI, ICU or hospital stay, or 30-day functional outcome.
Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.
Healthcare contributes significantly to global greenhouse gas (GHG) emissions, yet the environmental impact of sleep medicine, particularly the diagnosis and therapy of obstructive sleep apnea (OSA), remains poorly characterized. We systematically searched PubMed, Scopus, and Embase (2015-2025) for studies on OSA care reporting environmental metrics (carbon footprint, energy use, resource consumption) or healthcare resource utilization. Supplementary searches identified additional non-peer-reviewed sustainability-focused studies that have been presented at conferences. Of 19 primary peer-reviewed studies on OSA care and utilization, only one reported environmental metrics (telemedicine CO2 savings related to reduction in travel-related emissions). Supplementary sources revealed that OSA care has a measurable carbon footprint driven by disposable equipment, device electricity, and travel and that OSA diagnostics create significant solid waste with opportunities for waste reduction through the use of reusable equipment. This review shows that while the environmental impact of sleep medicine has been rarely studied to this date, available evidence suggests significant opportunities for sustainability through virtual care, home testing, and equipment optimization. Future research should incorporate environmental impact into the assessment of clinical pathways.
Alterations in circulating bile acids (BAs) have been reported in inflammatory bowel disease (IBD), but the consistency of these changes across clinically relevant comparisons remains unclear. Our goal was to investigate systemic BA alterations in IBD using a metabolomics meta-analysis with an exploratory analysis of BA-related gene expression as a supporting context. A systematic review and meta-analysis of 28 metabolomics studies examined blood BA profiles associated with IBD, IBD diagnosis, and disease activity assessment. Univariate analysis and logistic regression modeling of two independent IBD cohorts explored the blood BA-related genes and IBD. Across 28 studies that comprised 5056 IBD patients, 1721 healthy controls, and 314 non-IBD patients, 131 BAs were reported. Eight predefined clinical comparisons were eligible for the meta-analysis. Lower secondary BA levels were consistently observed in IBD patients compared with controls, between UC and CD, and in active versus remission patients. Deoxycholic acid, glycodeoxycholic acid, and taurodeoxycholic acid were frequently decreased, whereas glycocholic acid was increased in certain comparisons. Transcriptomics analyses revealed differential expression of several BA-related genes in blood, including SLC51A, ABCB4, and ACOT8, across the comparisons. Our findings identify consistent circulating BA alterations in IBD and highlight the relevance of blood BA for future biomarker research in the diagnosis and disease activity assessment.
INTRODUCTION: Congenital bile acid synthesis defects are rare autosomal recessive disorders that typically present in early infancy with cholestasis, progressive liver dysfunction, and, in severe cases, acute liver failure. These conditions may mimic other metabolic diseases detected in newborn screening, complicating early diagnosis. The AKR1D1 gene encodes Δ4-3-oxosteroid 5β-reductase, a key enzyme in primary bile acid synthesis, and pathogenic variants cause bile acid synthesis defect type 2 (OMIM #235555). CASE DESCRIPTION: We report a 3-month-old male infant with severe neonatal cholestasis and a history of elevated tyrosine levels in newborn screening. Pregnancy was high risk and unmonitored, with birth outside a hospital. Parental consanguinity was first-degree. Early metabolic evaluation showed transient normalization of tyrosine levels, but subsequent analyses revealed recurrent hyper-tyrosinemia. Urinary organic acids showed increased 4-hydroxyphenyl metabolites, with absent succinylacetone, excluding tyrosinemia type I. Progressive cholestasis developed, accompanied by coagulopathy, hyperbilirubinemia, hyperammonemia, and markedly elevated alpha-fetoprotein. Imaging revealed no structural liver abnormalities. Clinical exome sequencing identified a novel homozygous start-loss variant in AKR1D1, likely abolishing functional enzyme production. Metabolic studies confirmed increased urinary excretion of 3-oxocholenoic acids consistent with abnormal bile acid synthesis and supporting a diagnosis of bile acid synthesis defect type 2. Oral cholic acid therapy led to stabilization and improvement in clinical and biochemical parameters. DISCUSSION/CONCLUSION: This case illustrates the diagnostic complexity of neonatal cholestasis, particularly when initial metabolic findings suggest alternative etiologies. It highlights the importance of newborn screening as a tool for broader diagnostic suspicion and the critical role of early molecular diagnosis and multidisciplinary care. Timely recognition and targeted therapy can improve outcomes, prevent liver transplantation, and enable accurate genetic counseling, especially in consanguineous families.
BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.
BACKGROUND: Dermoscopy is a noninvasive imaging technique that is well-established in human dermatology, where it enhances the diagnosis of neoplastic, inflammatory, infectious, and alopecic skin disorders. In veterinary dermatology, its use is expanding yet remains heterogeneous and largely descriptive, despite growing evidence of conserved dermoscopic patterns across species. HYPOTHESIS/OBJECTIVES: To review the applications of dermoscopy in veterinary dermatology, and to provide a comparative analysis of dermoscopic features observed in dogs, cats, and horses in relation to corresponding findings in human dermatology. MATERIALS AND METHODS: A systematic review of the literature reporting dermoscopic findings in veterinary dermatology was conducted in accordance with PRISMA guidelines. PubMed, Scopus and Google Scholar were searched for studies published up to 30 July 2025. Eligible studies included original articles describing dermoscopic features in dogs, cats, or horses. Extracted data included species, dermatological condition, dermoscopic findings, device type and histopathological correlation, when available. Levels of evidence were assessed using the Oxford Centre for Evidence-Based Medicine criteria. RESULTS: Thirty studies met the inclusion criteria. Most were descriptive case reports or case series. Dermoscopy was applied to a wide range of conditions, including alopecias, parasitic infestations, dermatophytosis, neoplastic and sebaceous lesions, inflammatory dermatoses, and congenital vascular anomalies. Recurrent dermoscopic features showed strong similarities to those described in human dermatology, although species-specific anatomical differences influenced interpretation. CONCLUSIONS: Dermoscopy represents a valuable adjunct diagnostic tool in veterinary dermatology, with clear translational relevance. Standardisation of terminology and further prospective studies are required to support its broader clinical integration.