Search Results (2,637)

Objective: The purpose of this study was to investigate the knowledge, attitudes, and practices (KAPs), including ageism, of rehabilitation service providers regarding older adults with substance use disorders to examine the association between KAPs and ageism on the knowledge of rehabilitation providers and confidence in treating this population. Methods: An online survey was developed to assess providers’ familiarity with geriatric substance use disorders, attitudes towards aging, and perceived barriers to treatment. The survey included the Expectations Regarding Aging (ERA-12) tool to measure ageist attitudes. Data was collected from 25 rehabilitation healthcare providers across rehabilitation centers in North Carolina. Descriptive statistics and ERA-12 scoring were used to analyze the results. Results: Most (52.0%) respondents reported slight or moderate familiarity with specific risk factors for substance use disorders associated with older adults, and participants most commonly expressed ambivalence (48.0% indicated they were neither satisfied nor dissatisfied) with their training on this demographic. Barriers included a lack of specialized training, limited availability of age-appropriate treatment programs, and resistance to change. Negative attitudes towards aging and substance use disorders were prevalent among respondents. Providers indicated a need for enhanced education, clinical guidelines, and access to geriatric-trained professionals. Discussion: The findings highlight a critical need for specialized training for rehabilitation providers to improve care for older adults with substance use disorders. Addressing ageism, increasing awareness, and enhancing provider education are essential to improving treatment outcomes. Implementing targeted training programs and specialized resources could significantly enhance the quality of care for this underserved population. Full article

This study introduces the Machine Learning (ML)-Driven Pattern Synthesis for Digital Forensics in Synthetic Log Analysis (ML-PSDFA) framework to address critical gaps in digital forensics, including the reliance on real-world data, limited pattern diversity, and forensic integration challenges. A key innovation is the introduction of a novel temporal forensics loss ${\mathcal{L}}_{\mathrm{TFL}}$ in the Synthetic Attack Pattern Generator (SAPG), which enhances the preservation of temporal sequences in synthetic logs that are crucial for forensic analysis. The framework employs the SAPG with hybrid seed data (UNSW-NB15 and CICIDS2017) to create 500,000 synthetic log entries using Google Colab, achieving a realism score of 0.96, a temporal consistency score of 0.90, and an entropy of 4.0. The methodology employs a three-layer architecture that integrates data generation, pattern analysis, and forensic training, utilizing TimeGAN, XGBoost classification with hyperparameter tuning via Optuna, and reinforcement learning (RL) to optimize the extraction of evidence. Due to enhanced synthetic data quality and advanced modeling, the results exhibit an average classification precision of 98.5% (best fold 98.7%) 98.5% (best fold 98.7%), outperforming previously reported approaches. Feature importance analysis highlights timestamps (0.40) and event types (0.30), while the RL workflow reduces false positives by 17% over 1000 episodes, aligning with RL benchmarks. The temporal forensics loss improves the realism score from 0.92 to 0.96 and introduces a temporal consistency score of 0.90, demonstrating enhanced forensic relevance. This work presents a scalable and accessible training platform for legally constrained environments, as well as a novel RL-based evidence extraction method. Limitations include a lack of real-system validation and resource constraints. Future work will explore dynamic reward tuning and simulated benchmarks to enhance precision and generalizability. Full article

Knowledge graphs (KGs) represent a promising approach for detecting and correcting errors in automated audio and video transcripts. Yet the lack of accessible tools leaves human reviewers with limited support, as KG construction from media data often depends on advanced programming or natural language processing expertise. We present the Custom LLM Automated Relationship Extractor (CLARE), a system that lowers this barrier by combining context-aware relation extraction with an interface for transcript correction and KG refinement. Users import time-synchronized media, correct transcripts through linked playback, and generate an editable, searchable KG from the revised text. CLARE supports over 150 large language models (LLMs) and embedding models, including local options suitable for privacy-sensitive data. We evaluated CLARE on the Measure of Information in Nodes and Edges (MINE) benchmark, which pairs articles with ground-truth facts. With minimal parameter tuning, CLARE achieved 82.1% mean fact accuracy, exceeding Knowledge Graph Generation (KGGen, 64.8%) and Graph Retrieval-Augmented Generation (GraphRAG, 48.3%). We further assessed interactive refinement by revisiting the twenty-five lowest-scoring graphs for fifteen minutes each and found that the fact accuracy rose by an average of 22.7%. These findings show that CLARE both outperforms prior methods and enables efficient user-driven improvements. By streamlining ingestion, correction, and filtering, CLARE makes KG construction more accessible for researchers working with unstructured data. Full article

Background: Pediatric asthma is a multifactorial condition influenced by environmental, biological, and social determinants. The COVID-19 pandemic introduced new variables that may have affected the severity and management of asthma in children and adolescents, particularly through changes in healthcare access, treatment adherence, and exposure to environmental risk factors. Objective: To evaluate the association between asthma severity and various factors including nutritional status, corticosteroid use, COVID-19 vaccination, and pollutant exposure before and during the COVID-19 pandemic in a pediatric population. Methods: A retrospective analysis was conducted using 307 medical records of patients aged 3 to 17 years. Data collected included sociodemographic characteristics, nutritional indicators, history of corticosteroid use, vaccination status against COVID-19, and exposure to environmental pollutants. Asthma severity was assessed using the pulmonary score, and multiple statistical analyses, including logistic regression using the Bayesian Logistic Regression Model (BLRM), were employed to identify significant associations. Results: The analysis revealed a statistically significant impact of the pandemic on hospitalization rates (p = 0.0187) and the use of corticosteroids (p = 0.009), indicating changes in asthma management during this period. Notable differences were observed in the geographic distribution of mild versus severe asthma cases prior to the pandemic, associated with nutritional status and gender (p = 0.018). During the pandemic, breastfeeding history, body weight, and hospitalization emerged as significant predictors of asthma severity (p < 0.05). In addition, breastfeeding in young children (aged 3 to 6 years) and hospitalization were strongly associated with pulmonary scores, with significance values of 0.022 and 0.012, respectively, as identified by the BLRM. Conclusions: These findings suggest that the pandemic context influenced both the clinical course and management of pediatric asthma. Preventive strategies should consider individual and environmental factors such as nutrition, early-life health practices (e.g., breastfeeding), and equitable access to appropriate asthma care and vaccination. Tailoring pediatric asthma management to these variables may improve outcomes and reduce disparities in disease severity. Full article

Background: Repeat induced abortion (defined as ≥two lifetime procedures) is becoming more common worldwide, yet its independent influence on women’s psychological health remains contested, particularly in settings where access to modern contraception is restricted. Objectives: This review sought to quantify the burden of depression, anxiety, stress, and generic quality of life (QoL) among women with repeat abortions and to determine how barriers to contraceptive access alter those outcomes. Methods: Following the preregistered PRISMA-2020 protocol, PubMed, Embase and Scopus were searched from inception to 31 June 2025. Results: Eight eligible studies comprising approximately 262,000 participants (individual sample sizes up to 79,609) revealed wide variation in psychological morbidity. Prevalence of clinically significant symptoms ranged from 5.5% to 24.8% for depression, 8.3% to 31.2% for anxiety, and 18.8% to 27% for perceived stress; frequent mental distress affected 12.3% of women in neutral policy environments but rose to 21.9% under highly restrictive abortion legislation. Having three or more abortions, compared with none or one, increased the odds of depressive symptoms by roughly one-third (pooled OR ≈ 1.37, 95% CI 1.13–1.67). Contextual factors exerted comparable or stronger effects: abortions sought for socioeconomic reasons elevated depression odds by 34%, unwanted disclosure of the abortion episode increased depressive scores by 0.62 standard deviations, and low partner support raised them by 0.67 SD. At the structural level, every standard deviation improvement in a state’s reproductive rights index reduced frequent mental distress odds by 5%, whereas enactment of a near-total legal ban produced an absolute increase of 6.8 percentage points. QoL outcomes were less frequently reported; where measured, denied or heavily delayed abortions were associated with a 0.41-unit decrement on a seven-point life satisfaction scale. Conclusions: Psychological morbidity after abortion clusters where legal hostility, financial hardship, or interpersonal coercion constrain contraceptive autonomy while, in comparison, the mere number of procedures is a weaker predictor. Interventions that integrate stigma-free mental health support with confidential, affordable, and rights-based contraception are essential to protect well-being in women who experience repeat abortions. Full article

Background: The miniaturization of ureterorenoscopes increasingly enables atraumatic primary ureteroscopy, without ureteral dilation or presenting. This study aims to evaluate the feasibility and safety of primary ureteroscopy using the HU30M (6.3 Fr, HugeMed, Shenzhen HugeMed Medical Technical Development Co., Ltd., China), the smallest currently available ureteroscope Methods: We analyzed consecutive patients in whom primary ureteroscopy using the HU30M was performed or attempted, using prospectively collected in-hospital and 30-day follow-up data for retrospective evaluation. The primary outcome was the success rate of primary ostial intubation. Secondary outcomes included the stone-free rate (SFR) in patients with urolithiasis, incidence of in-hospital complications (Clavien–Dindo classification) and 30-day emergency readmission. Additionally, we conducted a propensity score-matched comparative analysis of the HU30M versus a contemporary 7.5 Fr digital single-use ureteroscope (PUSEN PU3033AH, Zhuhai Pusen Medical Technology Co., Ltd., China). Results: Between January and April 2025, primary ureteroscopy using the HU30M was performed or attempted in 34 patients, including four bilateral procedures. Primary ureteroscopy was defined as ureteroscopic access without prior stenting or dilation. Indications were diagnostic evaluation in 15 patients (44%), uretreroscopic stone treatment in 10 patients (29%) and endoscopic combined intrarenal surgery (ECIRS) in 9 patients (27%). Successful primary ostial intubation was achieved in 36 of 38 renal units (95%). Among urolithiasis cases, SFR was 17/19 (90%) in-hospital complications were limited to postoperative fever in two patients (6%) and no procedure-related 30-day emergency readmission occurred. In matched analyses, HU30M demonstrated significantly shorter operative times compared with the 7.5 Fr ureteroscope, while postoperative hemoglobin drop, inflammatory parameters and renal function were comparable. Conclusions: Primary ureteroscopy with HU30M is feasible and safe across diverse indications, achieving high success of atraumatic ostial access. Comparative analyses suggest procedural efficiency advantages and overall safety comparable to the current digital single-use ureteroscope standard. Full article

Background: Lumbar disk herniation is a common cause of low back pain and radiculopathy, significantly impacting patients’ life quality and functional capacity. Magnetic Resonance Imaging (MRI) remains the gold standard for its assessment due to its superior soft tissue contrast and multiplanar imaging capabilities. However, recent advances in spectral computed tomography (CT), particularly dual-energy CT (DECT), have introduced new diagnostic opportunities, offering improved soft tissue characterization. Objective: To evaluate the diagnostic performance of DECT in detecting and grading lumbar disk herniations using dedicated color-coded fat maps. Materials and Methods: A total of 205 intervertebral levels from 41 consecutive patients with lumbar symptoms were prospectively analyzed. All patients underwent both DECT and MRI within 3 days. Three radiologists with varying years of experience independently assessed DECT images using color-coded reconstructions. A five-point grading score was attributed to each lumbar level: 1 = normal disk, 2 = bulging/protrusion, 3 = focal herniation, 4 = extruded herniation, and 5 = migrated fragment. The statistical analysis included Pearson’s correlation for score consistency, Cohen’s Kappa for interobserver agreement, generalized estimating equations for a cluster-robust analysis, and an ROC curve analysis. The DECT diagnostic accuracy was assessed in a dichotomized model (grades 1–2 = no herniation; 3–5 = herniation), using MRI as reference. Results: A strong correlation was observed between DECT and MRI scores across all readers (mean Pearson’s r = 0.826, p < 0.001). The average exact agreement between DECT and MRI was 79.4%, with the highest concordance at L1–L2 (86.7%) and L5–S1 (80.4%). The interobserver agreement was substantial (mean Cohen’s κ = 0.765), with a near-perfect agreement between the two most experienced readers (κ = 0.822). The intraclass correlation coefficient was 0.906 (95% CI: 0.893–0.918). The ROC analysis showed excellent performance (AUC range: 0.953–0.986). In the dichotomous model, DECT demonstrated a markedly higher sensitivity than conventional CT (95.1% vs. 57.2%), with a comparable specificity (DECT: 99.0%; CT: 96.5%) and improved overall accuracy (98.4% vs. 90.0%). Subgroup analyses by age and disk location revealed no statistically significant differences. Conclusions: The use of DECT dedicated color-coded fat map reconstructions showed high diagnostic performance in the assessment of lumbar disk herniations compared to MRI. These findings support the development of dedicated post-processing tools, facilitating the broader clinical adoption of spectral CT, especially in cases where MRI is contraindicated or less accessible. Full article

Nepal is highly susceptible to natural hazards, including earthquakes, flooding, and landslides, all of which may occur independently or in combination. Climate change is projected to increase the frequency and intensity of these natural hazards, posing growing risks to Nepal’s infrastructure and development. To the authors’ knowledge, the majority of existing geohazard research in Nepal is typically limited to single hazards or localised areas. To address this gap, MiMapper was developed as a cloud-based, open-access multi-hazard mapping tool covering the full national extent. Built on Google Earth Engine and using only open-source spatial datasets, MiMapper applies an Analytical Hierarchy Process (AHP) to generate hazard indices for earthquakes, floods, and landslides. These indices are combined into an aggregated hazard layer and presented in an interactive, user-friendly web map that requires no prior GIS expertise. MiMapper uses a standardised hazard categorisation system for all layers, providing pixel-based scores for each layer between 0 (Very Low) and 1 (Very High). The modal and mean hazard categories for aggregated hazard in Nepal were Low (47.66% of pixels) and Medium (45.61% of pixels), respectively, but there was high spatial variability in hazard categories depending on hazard type. The validation of MiMapper’s flooding and landslide layers showed an accuracy of 0.412 and 0.668, sensitivity of 0.637 and 0.898, and precision of 0.116 and 0.627, respectively. These validation results show strong overall performance for landslide prediction, whilst broad-scale exposure patterns are predicted for flooding but may lack the resolution or sensitivity to fully represent real-world flood events. Consequently, MiMapper is a useful tool to support initial hazard screening by professionals in urban planning, infrastructure development, disaster management, and research. It can contribute to a Level 1 Integrated Geohazard Assessment as part of the evaluation for improving the resilience of hydropower schemes to the impacts of climate change. MiMapper also offers potential as a teaching tool for exploring hazard processes in data-limited, high-relief environments such as Nepal. Full article

Introduction: Tuberculosis (TB) remains a public health concern, and people at risk for TB are hesitant to seek care. The first South African National TB prevalence survey, conducted in 2017–2019, found that most participants with TB symptoms did not seek care for TB. In 2022, an estimated 23% of people with TB in South Africa were undiagnosed, contributing to the country’s burden of “missing” TB cases. This study explores health-seeking behaviour among people with TB (PwTB) in South Africa, focussing on barriers and facilitators to care-seeking and the quantification of TB-related stigma from a patient and community perspective. Methods: We conducted a mixed-method study in the City of Johannesburg (COJ) Metropolitan Municipality from February to March 2022. PwTB aged 18 and older initiating TB treatment for microbiologically confirmed pulmonary TB were recruited from three primary healthcare facilities in the COJ. After providing written informed consent, they participated in a one-time, in-depth, face-to-face interview. The interviews were digitally recorded and conducted by trained facilitators. We used thematic analysis with deductive approaches to develop themes. We used the Van Rie TB stigma assessment scale to quantify perceived stigma. Results: We interviewed 23 PwTB with an overall median age of 39 years and 14 (61%) males. Patient-level barriers to accessing TB care included visiting traditional healers and pharmacists before their TB diagnosis; wrong or missed diagnosis by private doctors; work commitments; scarcity of resources to attend the clinic or walk long distances; perceived and experienced stigma; and a lack of TB knowledge. Facility-level barriers included long clinic queues and uncertainty about where to receive TB care in the clinic. Facilitators for TB care-seeking included being in contact with someone who had TB, receiving encouragement from family, or having knowledge about TB transmission and early diagnosis. The overall median total stigma score among 21 PwTB was 53 (IQR: 46–63), with median community and patient stigma scores of 25 (IQR: 22–30) and 31 (IQR: 21–36), respectively. Conclusions: We found important considerations for the TB programme to improve the uptake of services. Since PwTB consult elsewhere before visiting a facility for TB care, TB programmes could establish private–public partnerships. TB programmes could also increase TB awareness in the community, especially among males, and mobile clinics could be considered to assist with TB case detection and treatment provision. Applying behavioural design techniques and co-designing interventions with patients and providers could improve TB health-seeking behaviours. Full article

Introduction: YouTube™ is a widely accessible platform with unfiltered medical information. This study aimed to evaluate the educational value and reliability of YouTube™ videos on Hyperthermic Intraperitoneal Chemotherapy (HIPEC) for advanced epithelial ovarian cancer treatment. Methods: YouTube™ videos were searched using the keywords “ovarian cancer”, “debulking surgery”, “hyperthermic”, and “HIPEC”. Patient Education Materials Assessment Tool for Audiovisual Content (PEMAT A/V) score, DISCERN, Misinformation Scale, and the Global Quality Scale (GQS) were employed to assess the clarity, quality, and reliability of the information presented. Results: Of the 150 YouTube™ videos screened, 71 were suitable for analysis and categorized by target audience (general public vs. healthcare workers). Most (57, 80.2%) were uploaded after the “Ov-HIPEC” trial (18 January 2018), with a trend toward more videos for healthcare workers (p = 0.07). Videos for the general public were shorter (p < 0.001) but received more views (p = 0.06) and likes (p = 0.09), though they were of lower quality. The DISCERN score averaged 50 (IQR: 35–60), with public-targeted videos being less informative (p < 0.001), a trend mirrored by the Misinformation Scale (p < 0.001) and GQS (p < 0.001). The PEMAT A/V scores showed 80% Understandability (IQR: 62–90) and 33% Actionability (IQR: 25–100), with no significant difference between groups (p = 0.15, p = 0.4). Conclusions: While YouTube™ provides useful information for healthcare professionals, it cannot be considered a reliable source for patients seeking information on HIPEC for ovarian cancer. Many videos contribute to misinformation by not properly explaining treatment indications, timing, adverse effects, multimodal approaches, or clinical trial findings. Full article

Background/Objectives: Spanish-speaking patients face persistent barriers in accessing equitable audiological care, particularly when standardized language-appropriate tools are lacking. Two Spanish-language sentence recognition tests, the Spanish AzBio Sentence (SAzB) and the Latin American Hearing in Noise Test (LAH), are commonly used to evaluate speech perception in adults with hearing loss. However, performance differences between these measures may influence referral decisions for hearing intervention, such as cochlear implantation. This study compared test performance under varying noise and spatial conditions to guide appropriate test selection and reduce the risk of misclassification that may contribute to healthcare disparities. Methods: Twenty-one bilingual Spanish/English speaking adults with normal bilateral hearing completed speech perception testing using both the SAzB and LAH. Testing was conducted under two spatial configurations: (1) speech and noise presented from the front (0° azimuth) and (2) speech to the simulated poorer ear and noise to the better ear (90°/270° azimuth). Conditions included quiet and three signal-to-noise ratios (+10, +5, and 0 dB). Analyses included paired t-tests and one-way ANOVAs. Results: Participants scored significantly higher on the LAH than on the SAzB across all SNR conditions and configurations, with ceiling effects observed for the LAH. SAzB scores varied by language dominance, while LAH scores did not. No other differences were observed based on any further demographic information. Conclusions: The SAzB provides a more challenging and informative assessment of speech perception in noise. Relying on easier tests like the LAH may obscure real-world difficulties and delay appropriate referrals for hearing loss intervention, including cochlear implant evaluation. Selecting the most appropriate test is critical to avoiding under-referral and ensuring Spanish-speaking patients receive equitable and accurate care. Full article

Urban mobility plays a vital role in shaping sustainable cities, yet the effectiveness of public transportation is often undermined by poor last-mile connectivity (LMC). In the National Capital Region (NCR) of Delhi, despite the Delhi Metro Rail serving as a key transit system, limited integration with surrounding areas hinders accessibility, which particularly affects women, elderly adults, and socioeconomically disadvantaged groups. This study evaluates LMC performance at two key metro stations, Nehru Place and Botanical Garden, using a mixed-methods approach that includes user surveys, spatial survey, thematic analysis, and infrastructure scoring across five critical pillars: accessibility, safety and comfort, intermodality, service availability, and inclusivity. The findings communicate notable contrasts. Botanical Garden exhibits strong intermodal linkages, pedestrian-friendly design, and supportive signage, while Nehru Place indicates a need for infrastructural improvements, safety advancement and upgrades, and strengthened universal design features. These disparities limit effective metro usage and discourage a shift from private to public transport. The study highlights the importance of user-centered, multimodal solutions and the need for cohesive urban governance to address LMC gaps. By identifying barriers and opportunities for improvement, this research paper contributes to the formulation of more inclusive and sustainable urban transport strategies in Indian metropolitan regions. Full article

Spatial accessibility is a key principle in urban studies, shaping how people reach amenities and services across cities. While most research concentrates on large metropolitan areas and central urban services, small and medium-sized cities and their main amenities remain less studied. To bridge this gap, this study explores spatial accessibility to public amenities in relation to population density in Odense, a medium-sized city known for its compact layout and robust infrastructure supporting walking, cycling, and public transport. Despite Odense’s proactive planning and multimodal transport network, marked accessibility inequalities still exist, especially in peripheral neighbourhoods. This research uses a data-driven approach combining network-based travel time analysis with grid-cell-based spatial visualisation. Additionally, a multi-criteria accessibility scoring framework is introduced, including indicators such as amenity density, diversity of services, temporal thresholds for walking and cycling, and population distribution. The results show an uneven accessibility landscape, with significant gaps in outer districts, highlighting the limitations of uniform planning thresholds. By applying spatial analytical principles, the study uncovers embedded socio-spatial inequalities in everyday urban access. These insights offer practical guidance for planners and policymakers, underscoring the importance of context-sensitive multimodal infrastructure and decentralised service provision to support sustainable urban growth. Full article

Background/Objectives: A high-performing blood biomarker (BBM) test for Alzheimer’s disease (AD) represents an accurate, accessible, and scalable tool to aid healthcare professionals (HCPs) evaluating patients presenting with signs or symptoms of mild cognitive impairment (MCI) or dementia. However, implementation of AD blood tests into clinical practice has not been extensively evaluated. The objective of this study was to assess the implementation of the multi-analyte PrecivityAD2™ blood test (C2N Diagnostics, LLC, St. Louis, MO, USA) into the clinical workflow of memory care clinics. Methods: A total of 8 HCPs (neurologists, geriatricians, geriatric psychiatrists) who served as site directors from 8 outpatient sites that evaluated 203 cognitively symptomatic patients were included in this sub-study of the real-world QUIP II Study (NCT06025877). Implementation of this blood test was assessed through surveying these HCPs using published frameworks including the Technology Acceptance Model, net promoter score, and forced choice preference questions. These assessments were analyzed using Wilcoxon signed-rank test, Fisher’s Exact test, and Wilcoxon signed-rank test, respectively. Results: HCPs reported acceptance scores that averaged 9.6 out of 10 (p < 0.0001, effect size 0.840): the test’s contribution to clinical decision-making as well as the ease of understanding test results received the highest ratings. The net promoter score was 75 (p < 0.0001), exceeding the typical benchmark of 30 reported as good levels of satisfaction in healthcare settings. The APS2 results and individual blood analyte results were rated with similar preference around their roles in HCP clinical decision-making. Conclusions: The results indicate early evidence of user acceptance and recognition by HCPs that this AD blood test can personalize the clinical care pathway for evaluating cognitively symptomatic patients. Full article

Background/Objectives: Mpox, a viral disease marked by distinctive skin lesions, has emerged as a global health concern, underscoring the need for scalable, accessible, and accurate diagnostic tools to strengthen public health responses. This study introduces ITMA’INN, an AI-driven healthcare system designed to detect Mpox from skin lesion images using advanced deep learning. Methods: The system integrates three key components: an AI model pipeline, a cross-platform mobile application, and a real-time public health dashboard. We leveraged transfer learning on publicly available datasets to evaluate pretrained deep learning models. Results: For binary classification (Mpox vs. non-Mpox), Vision Transformer, MobileViT, Transformer-in-Transformer, and VGG16 achieved peak performance, each with 97.8% accuracy and F1-score. For multiclass classification (Mpox, chickenpox, measles, hand-foot-mouth disease, cowpox, and healthy skin), ResNetViT and ViT Hybrid models attained 92% accuracy (F1-scores: 92.24% and 92.19%, respectively). The lightweight MobileViT was deployed in a mobile app that enables users to analyze skin lesions, track symptoms, and locate nearby healthcare centers via GPS. Complementing this, the dashboard equips health authorities with real-time case monitoring, symptom trend analysis, and intervention guidance. Conclusions: By bridging AI diagnostics with mobile technology and real-time analytics, ITMA’INN advances responsive healthcare infrastructure in smart cities, contributing to the future of proactive public health management. Full article