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PubMed2026

Factors influencing the enhancement of the new iron triangle in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans↗

PubMed2026

A Sentiment-Based Comparison of AI- and Physician-Generated Empathic Statements in Palliative Care.

CONTEXT: Empathic communication promotes trust in patient-provider relationships. As healthcare integrates artificial intelligence (AI) into patient communication, we have yet to understand how these models' communication compares to that of physicians. OBJECTIVES: Our primary objectives were to examine patient preferences for AI-generated vs. palliative care physician-generated empathic statements addressing fear and anxiety around cancer treatment, and to analyze associations between linguistic features and patient preferences. METHODS: We conducted a secondary analysis of the PALL-AI trial, a randomized controlled survey comparing cancer patients' preferences of AI- to physician-generated empathic statements. Physicians and AI were provided the same prompt with a maximum sentence length. Patient preferences for each statement were measured in blinded surveys. We analyzed sentiment of the statements using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and the National Research Council Canada (NRC) Emotion Lexicon. We evaluated associations between sentiment scores and patient preferences using Spearman's correlation coefficients. RESULTS: A total of 105 patients completed blinded surveys, preferring the AI-generated statement 72.4% of the time. VADER sentiment analysis showed all three AI statements displayed positive sentiment, while all three physician statements displayed negative sentiment. Controlling for statement length, AI statements used twice as many positive words as human statements. However, they contained a similar number of negative words. Of the eight NRC emotions, "trust" and "joy" demonstrated the strongest correlations with patient preference. CONCLUSION: Patients preferred AI-generated statements around cancer care over those from palliative care physicians when standardized for prompt and statement length. Analysis shows AI-generated statements contain more positive language which may be the factor driving patient preference toward AI.

Humans↗

PubMed2026

Advancing nursing education through social and emotional learning: A systematic review guided by the Collaborative for Academic, Social, and Emotional Learning framework.

BACKGROUND: With Generation Z entering the nursing workforce in growing numbers, strengthening social and emotional learning is critical for academic success, professional adaptation, and safe practice. However, the existing evidence remains fragmented because of varied interventions and inconsistent approaches. OBJECTIVES: This systematic review examined (1) the social and emotional learning essential for nursing students and nurses within the Collaborative for Academic, Social, and Emotional Learning framework, (2) their impact on educational and clinical outcomes, and (3) implications for advancing nursing education and practice. METHODS: Following Joanna Briggs Institute methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, five international (PubMed, EMBASE, CINAHL, PsycINFO, Cochrane) and three Korean (RISS, KoreaMed, KMBASE) databases were searched up to June 2025. Eighteen studies involving 2,952 participants met the inclusion criteria, including quasi-experimental quantitative studies, descriptive quantitative studies, qualitative studies, and mixed-methods studies. The methodological quality of the included studies was appraised using the Mixed Methods Appraisal Tool. RESULTS: Within the Collaborative for Academic, Social, and Emotional Learning framework, relationship skills and self-management were the most frequently studied competencies, emphasizing teamwork, communication, and stress regulation. Self-awareness and social awareness were underexplored, despite their importance in empathy, resilience, and reflective practice. Responsible decision-making was the least studied competency, despite its importance in ethical reasoning. Social and emotional learning was consistently associated with enhanced adaptation, communication, leadership, relationships, and clinical performance. Effective strategies included blended learning, simulation, reflective activities, and mentorship, which are aligned with Generation Z's learning preferences. CONCLUSION: Although social and emotional learning integration is associated with improvements in educational and clinical outcomes in nursing, current research has largely centered on relational and stress-related competencies while underrepresenting responsible decision-making. To cultivate reflective, empathetic, and ethically grounded nurses, curricula should integrate social and emotional learning through a balanced and structured approach. REGISTRATION: This study was registered on PROSPERO (ID: CRD420251005683).

Humans↗

PubMed2026

Effectiveness of transcranial direct current stimulation with and without positive mood induction on worry and transdiagnostic cognitive-emotional processes: A randomized controlled trial.

The present study investigated the effectiveness of transcranial direct current stimulation (tDCS), with and without positive mood induction, on worry and key transdiagnostic cognitive-emotional processes, including attentional bias, working memory, problem solving, and emotion regulation, in individuals with high levels of worry. This single-blind randomized controlled trial included 45 individuals with high levels of worry. After a structured clinical interview, participants were randomly assigned, with gender balancing, to one of three groups: (1) tDCS alone, (2) tDCS combined with positive mood induction, or (3) a sham control group. Outcome measures were administered at three time points (pretest, posttest, and one-month follow-up) and assessed attentional bias (Dot Probe Task), working memory (1-back task), problem solving (Tower of London task), emotion regulation (Gross's Emotion Regulation Questionnaire), and worry severity (Penn State Worry Questionnaire; PSWQ). Repeated-measures ANOVA showed that both active groups (tDCS alone and tDCS + positive mood induction) significantly improved attentional bias, worry, working memory, problem solving, and emotion regulation compared to controls (p < 0.05). The combined intervention produced significantly greater gains than tDCS alone in working memory, problem solving, emotion regulation (p < 0.05), and reductions in attentional bias and worry (p < 0.001). All effects persisted at one-month follow-up (p < 0.05). tDCS reduces worry and attentional bias and enhances cognition and emotion regulation in individuals with high levels of worry. The combined intervention produced larger and more sustained improvements than tDCS alone across the assessed behavioral outcomes. These findings support further investigation of combining tDCS with structured positive mood induction while the mechanisms underlying the additional benefits remain to be established.

Humans↗

PubMed2026

Effects of sub-anesthetic doses of esketamine on immune function and postoperative negative emotions in acoustic neuroma patients: a randomized clinical trial.

BACKGROUND: Patients undergoing acoustic neuroma (AN) surgery often experience postoperative negative emotions, including anxiety, depression, and immune function suppression. This trial evaluated whether perioperative sub-anesthetic esketamine improves early postoperative negative emotions and immune function. METHODS: In this single-center, double-blind, randomized trial, 84 patients scheduled for AN surgery were assigned to esketamine (n = 42) or placebo (n = 42). The esketamine cohort received a continuous intravenous infusion of esketamine at 0.2 mg·kg-1·h-1 during anesthesia, followed by 1 mg·kg-1 esketamine as an adjuvant in patient-controlled intravenous analgesia (PCIA). The placebo group received saline. The primary outcome was the incidence of depression on postoperative day (POD1), defined as a Hospital Anxiety and Depression Scale-Depression subscale (HADS-D) score > 7. RESULTS: Seventy-seven patients completed the study (39 in the esketamine group, 38 in the placebo group). Esketamine significantly reduced the incidence of depression at POD1 (7.7% versus 31.6%; relative risk 0.24, 95% CI: 0.08-0.80, p = 0.008) and POD3 (0.0% versus 15.8%, relative risk 0.00, 95% CI: 0.00-0.47, p = 0.031) compared with placebo. The incidences of anxiety on POD1 and 3 and sleep disturbances on POD1 were also significantly reduced (p < 0.05). Notably, no significant differences were observed between the two groups in terms of immune function, postoperative pain scores, or intraoperative morphine equivalent. Adverse events did not differ between the groups. CONCLUSION: Perioperative sub-anesthetic esketamine reduced postoperative depression and anxiety, and improve sleep quality after AN surgery, without significant effects on early immune function or acute postoperative analgesia. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2400084537.

Humans↗

PubMed2026

Game-Based Intervention for Bullying: Assessing the Efficacy of the REThink Therapeutic Game in Primary School Children.

Children's mental health issues can have a lasting effect into adulthood, including enhanced risks for their social and emotional development, as well as their academic performance and overall behavior. Worldwide nearly 1 billion children are affected by the bullying phenomenon, with social, emotional, and economic consequences. In this vein, our study aimed to analyze the effect of the therapeutic game REThink on the improvement of emotion regulation abilities and the reduction of both bullying behavior and victimization in primary school children. Our sample consisted of 75 children who were voluntarily enrolled by their parents, and randomly assigned to the intervention group (n = 38) or to the control group (n = 37). They completed the baseline assessment consisting of emotion regulation, irrationality, bullying and victimization behavior measurements, then the children from the intervention group played the therapeutic game REThink. Four weeks later, after completing each level twice, every participant had completed the same questionnaires at the post-test assessment. The results indicated significant changes across victimization for children who were exposed to verbal, physical or social bullying, increased emotional control and lower levels of irrationality, low frustration tolerance to work and demandingness, with small to medium effect size improvements for the REThink game group compared to the control group. The REThink therapeutic game proved to be a promising intervention tool for reducing victimization effects and irrationality, and improving emotion regulation abilities in primary school children. Future research could improve on these results by addressing the timeline stability limit.

Humans↗

PubMed2026

The effect of tDCS on emotion-related risk-taking behavior and delay discounting in adults with ADHD.

INTRODUCTION: Adults with Attention Deficit Hyperactivity Disorder (ADHD) often engage in risky behaviors due to impaired decision-making processes. This study aims to investigate the effects of transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) on emotion-related risk-taking behavior and delay discounting in adults with ADHD. METHODS: Thirty adults with ADHD underwent three tDCS conditions, administered in a randomized order with at least one week between sessions: (1) left dlPFC anode/right vmPFC cathode, (2) left dlPFC cathode/right vmPFC anode, and (3) sham stimulation. In each session, participants completed the Delay Discounting Task (DDT) and the Modified Balloon Analogue Risk Task (mBART) under three emotional conditions (neutral, positive, and negative) which were induced using emotionally congruent photographs and sounds. Galvanic skin responses (GSR) were also recorded. In the DDT, both area under the curve (AUC) values and log-transformed discounting rates (log k) were calculated for small, medium, and large reward magnitudes (RM). Exploratory electric field modeling was also performed to characterize current distribution. RESULTS: The findings demonstrated task-specific effects of tDCS on decision-making. Although no overall tDCS effect was observed on DDT performance, significant tDCS × RM interactions emerged, particularly for smaller rewards. In contrast, exploratory analyses suggested that tDCS affected all mBART scores. Emotional condition did not influence consistently behavioral performance in either task, whereas both emotional stimulation and tDCS significantly affected GSR responses. However, exploratory electric field modeling indicated a broad prefrontal current distribution extending beyond the intended cortical targets. CONCLUSIONS: These findings suggest preliminary evidence that prefrontal tDCS can influence risk-related decision-making and autonomic responses in adults with ADHD. However, its effects on delay discounting appear to be context-dependent and limited to specific RMs. Future studies combining neuroimaging with individualized electric field modeling are needed to clarify the neural mechanisms underlying the observed effects of tDCS and to optimize stimulation protocols in adults with ADHD.

Humans↗

PubMed2026

Angiotensin II regulates anxiety and social-affective top-down and bottom-up attention control in a sex-dependent manner.

BACKGROUND: The renin-angiotensin system (RAS) has been increasingly recognized as potent modulator of cognitive and affective functions, with angiotensin II type 1 receptor (AT1R) antagonists emerging as repurposing candidate for anxiety and stress-related disorders. However, it remains unclear whether transient AT1R blockade modulates emotional attentional control and whether these effects are sex-dependent. METHODS: We conducted a preregistered, randomized, double-blind, placebo-controlled pharmacological eye-tracking study in 79 healthy adults (males and females) and determined effects of transient AT1R blockade via losartan (50 mg) on emotional attention control using a validated anti-saccade paradigm with social (emotional faces) and non-social stimuli. Treatment effects on state anxiety and oculomotor responses were characterized using traditional metrics and a novel trial-history informed dynamic control framework. RESULTS: Losartan reduced state anxiety irrespective of sex but induced sexually dimorphic effects on attentional control. In females, losartan enhanced performance by reducing endpoint error without altering latency. Conversely, in males, losartan increased endpoint error and prolonged latency of the first correct saccade. Trial-history analyses revealed losartan reduced error probabilities following errors and repeat trials in both sexes. Yet, following correct trials, females receiving losartan maintained lower error probabilities, while males exhibited higher errors, potentially reflecting failure to disengage from effortful control. CONCLUSIONS: The RAS modulates anxiety and attentional control, the latter sex-dependently. AT1R blockade reconfigures attentional processing and adaptive control, suggesting sex-specific therapeutic potential in disorders characterized by excessive anxiety and attentional dysregulation. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov; https://clinicaltrials.gov/;NCT06329050.

Humans↗

PubMed2026

The Meaning and Significance of Breastfeeding for Biological Mothers of Children with Cleft Lip and/or Palate.

INTRODUCTION: Given the functional, emotional, and symbolic challenges imposed by cleft lip and/or palate (CL/P) on exclusive breastfeeding (EBF), mothers often experience early breastfeeding cessation with impacts on maternal identity and the mother-infant bond. This study aimed to explore the meanings, feelings, and experiences of mothers of children with CL/P regarding breastfeeding in the face of these adversities. METHODS: This qualitative study applied the Clinical-Qualitative Method as proposed by Turato. Six in-depth semistructured interviews were conducted with biological mothers of children with CL/P, recruited from a specialized craniofacial reference center in Brazil. Data were analyzed using a qualitative content analysis approach, grounded in psychodynamic concepts from the Medical Psychology theoretical framework. RESULTS: Based on the analysis of the collected material, three analytical categories were identified and constructed: (1) "Existential conflict regarding the inability to fulfill the ideal maternal role"; (2) "Duality between the need and the fear of caregiving"; and (3) "The anguish experienced between tangible and intangible support during breastfeeding."Conclusions:Although the inability to EBF in children with CL/P generates emotional distress, motherhood is reimagined through adaptive forms of care and bonding, highlighting gaps in institutional support and the need for more humanized, emotionally sensitive health practices.

Humans↗

PubMed2026

A randomized trial of omega-3 fatty acids plus inositol versus N-acetylcysteine for the treatment of depression and mania in emotionally dysregulated youth age 5-17 with and without autism traits.

The aim of this study was to assess the effectiveness of the nutraceutical treatments combined omega-3 fatty acid plus inositol (O3I) versus N-acetylcysteine (NAC) in children and adolescents with emotional dysregulation and the impact of the co-occurrence of autism traits (AT). Participants were male and female children (5-17) with emotional dysregulation and the presence/absence of AT, as defined by Child Behavior Checklist score, randomized to receive open-label O3I (1020 mg EPA and 1000-2000 mg Inositol) or NAC (1800-2700 mg) daily for 6 weeks. Clinicians measured severity and improvement of depression and mania with the NIMH Clinical Global Improvement Scale (CGI). Parents completed Parent-Youth Mania Rating Scale (P-YMRS) and Children's Depression Inventory (CDI). Both O3I and NAC resulted in modest improvements in mania and depression and did not differ significantly in between group comparison in their effectiveness. Participants taking O3I, but not NAC, demonstrated statistically significant within group improvement in depression per CDI. Participants taking NAC had a greater decrease in P-YMRS scores versus O3I, but the difference did not reach statistical significance. In the presence of AT, NAC was more effective than O3I for mania but not for depression. Further, participants taking NAC, but not O3I, demonstrated significant within group improvement in SRS and BRIEF scores. These results suggest that O3I and NAC may be beneficial for mania and depression in youth, with trends towards O3I more effective for depression and NAC more effective for mania. The presence of AT in youth with emotional dysregulation may moderate the impact of NAC.

Humans↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

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PubMed2026

How AI-supported intelligent systems support infection prevention and control training in healthcare: A systematic review of educational functions and outcomes.

AIMS: Artificial intelligence (AI)-supported intelligent systems have been increasingly incorporated into infection prevention and control (IPC) education and training, primarily to support the monitoring of observable behaviors and the provision of feedback. However, existing evidence has focused largely on short-term compliance outcomes, with limited synthesis of the educational role of AI-supported intelligent systems in supporting sustained IPC competence. This systematic review examined how AI-supported intelligent systems have been designed and used to support IPC education and training, with a focus on system characteristics, educational functions, and reported outcomes. DESIGN: A systematic literature search was conducted across the PubMed/MEDLINE, Embase, Cochrane, and CINAHL databases. DATA SOURCES: A total of 18 studies met the inclusion criteria. Findings were qualitatively synthesized according to system design characteristics, educational functions, and outcome domains. REVIEW METHODS: Methodological quality was appraised using the Mixed Methods Appraisal Tool. RESULTS: Most AI-supported intelligent systems focused on hand hygiene and relied on fully automated monitoring systems to capture behaviors and provide performance feedback. Educational functions were predominantly limited to performance assessment, automated feedback, and reminders. Outcomes were mainly measured using compliance or performance metrics, whereas sustained behavioral change and decision quality were rarely assessed. CONCLUSIONS: AI-supported intelligent systems have been used primarily to reinforce short-term IPC performance and compliance. However, their current applications for supporting sustained competence over time remain limited. The findings of this review suggest that AI-supported intelligent systems may serve as maintenance-oriented educational support by extending learning beyond initial instruction through repeated practice and feedback. Future research should prioritize outcome measures that capture the durability of performance and decision-making processes to better align AI-supported intelligent systems used in IPC education and training with the educational demands of clinical practice.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

A systematic review and meta-analysis of the late positive potential and internalizing psychopathology.

The present study leveraged the Hierarchical Taxonomy of Psychopathology (HiTOP) framework to conduct a systematic meta-analysis to determine the association between the late positive potential (LPP) index of emotional reactivity and internalizing psychopathology. PRISMA guidelines were followed. Articles were identified through PubMed, APA PsycInfo, and Web of Science online platforms in May 2025. Included articles examined associations between the LPP to positive and/or negative stimuli and internalizing psychopathology. Risk of bias and publication bias were assessed. Results were examined for individual disorders, distress and fear subfactors, and the internalizing spectrum using two approaches: standard analyses that examined aggregate effects and hierarchical analyses that examined direct and indirect relationships. We conducted moderator analyses for sample, task design, LPP quantification, and psychopathology measurement. We included 63 studies across 5,360 participants (Mage = 19.65, SD = 11.1; 58.7% female). In standard meta-analyses, depression was associated with a smaller LPP to positive stimuli (r = -.06, 95% confidence interval [CI; -.12, -.003]). Specific phobia was associated with a larger LPP to negative stimuli (r = .21, 95% CI [.02, .37]). Distress was associated with a smaller LPP to both positive (r = -.12) and negative (r = -.11) stimuli when measured via clinical interview, and fear was associated with a larger LPP to negative stimuli (r = .10, 95% CI [.03, .16]). Hierarchical analyses indicated that the depression results were specific to the disorder, whereas the fear disorder-level results were due to the higher order fear subfactor. The LPP demonstrates discriminant relationships with distress and fear disorders and subfactors. Results were largely robust against methodological factors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

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.

Humans↗

PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans↗