AI News Archive: July 27, 2026 — Part 14
Sourced from 500+ daily AI sources, scored by relevance.
- What Patients Reward and Punish in Physician Communication: A Framework-Based Analysis of 62,319 Indian Reviews
Background: Patient-generated online reviews contain detailed accounts of physician communication that remain systematically underused in health services research. Prior computational analyses have either applied service quality frameworks without grounding in clinical communication theory, or have been geographically and specialty-restricted. Objective: To examine which physician communication dimensions predict patient recommendation, switching intent, and retention across specialties and cities in India. Methods: We analyzed 62,319 patient reviews from the Practo platform (10 cities, 8 specialties) coded against established clinical communication frameworks, the Kalamazoo Consensus Statement, Calgary-Cambridge Guide, and SPIKES protocol, adapted into a 12-dimension codebook. Expert confirmatory review on 200 stratified reviews yielded 98.5% agreement between reviewer and model labels across 11 communication dimensions. Binary recommendation was designated the primary outcome; recommendation intensity is reported as secondary. Logistic regression with 1,000 bootstrap iterations examined associations between communication dimensions and recommendation and switching intent, adjusting for treatment outcome, cost, wait time, and specialty. Results: Reassurance (OR 2.07, 95% CI 1.86-2.42) and empathy (OR 1.89, 95% CI 1.79-2.00) were the strongest positive predictors of recommendation. Excessive directiveness (OR 0.62, 95% CI 0.60-0.64) and rushedness (OR 0.65, 95% CI 0.64-0.67) were the dominant negative predictors; directiveness was present in 33.3% of switching-intent reviews. Cost asymmetry was pronounced: cost concerns reduced recommendation rates by 54.2 percentage points; positive cost comments increased recommendation by 6.2 points. Specialty variance in recommendation intensity exceeded city variance (ratio 2.63). Conclusions: Excessive directiveness and rushedness were the communication behaviors most strongly associated with adverse behavioral outcomes in this corpus; reassurance and empathy are the strongest drivers of recommendation. These effects are modified by specialty context in ways that align with Kalamazoo, Calgary-Cambridge, and SPIKES theoretical predictions. The specialty-stratified findings provide a direct empirical basis for competency-based communication curricula in undergraduate and postgraduate medical education.
- The Impact of Self-Reported Health Factors on Behavioural Difficulties in School-Aged Children: Findings from the HAPPEN Pan-Wales Cohort Using Data Linkage
This study aimed to examine factors associated with behavioural difficulties among school-aged children (aged 7 -11) using self-reported survey data linked with education data from a national cohort study of over 50,000 children (the HAPPEN national cohort) in Wales, UK between 2014 and 2024. Data include self-reported health and wellbeing linked to additional learning needs (ALN) status collected from education data in Wales. Measures included self-reported time spent on screens, frequency of sugary snack, fizzy drink and takeaway food consumption, physical activity levels, sleep duration and behavioural difficulties (as measured by the Me and My Feelings Survey). Associations were analysed using descriptive trends, K-means cluster analysis and multivariate regression modelling. Findings showed a rise in behavioural difficulties during and post Covid, which are now improving in Wales. Cluster analysis identified that children with poor sleep and high takeaway and fizzy drinks dietary habits had the highest levels of behavioural difficulties, a trend that remained significant after adjusting for all potential confounders. Physical activity associated with reduced behavioural difficulty, with 5-6 days of activity associated with the lowest difficulty scores. These findings suggest that behavioural difficulty is driven by health behaviours especially sleep and diet rather than single factors. The results highlight the need for integrated public health approaches that address dietary quality and sleep hygiene rather than focusing on single factors in isolation. Promoting more balanced daily activity patterns, promoting good sleep routines, improving food environments and building movement into the school day may have important benefits for childrens behaviour.
- Patterns of healthcare use in people with narcolepsy: a population-based cohort study in England
People with narcolepsy experience delays in diagnosis and inconsistent post-diagnosis care, but the pattern and scale of their healthcare use is poorly described. In this population-based cohort study, we used primary care and linked hospital activity data to compare healthcare use in people with narcolepsy (n=2,772) and a matched comparison group in England (n=13,860). Narcolepsy was defined by a first coded record in primary care or admitted care data between 02 January 1998 and 31 December 2019; this date was the index date for both groups. People with narcolepsy had approximately double the rate of healthcare use in the period from five years before to five years after the index date. Annually, this corresponded on average to an additional 1.9 (95% confidence interval (CI) 1.8-2.0) outpatient events, 0.36 (95% CI 0.30-0.42) admitted patient care events, 0.25 (95% CI 0.22-0.29) Accident & Emergency events and 4.3 (95% CI 3.9-4.7) primary care events per person. Service use in all settings peaked at index and remained elevated for at least 15 years either side. The elevated rates of possible-sleep related outpatient events (respiratory, neurology paediatric, and ear nose & throat) peaked in the year including and after the index date, at 1.50 (95% CI 1.41-1.59); before declining to <0.5 visits per person-year after five years. Our findings of sustained elevated use of healthcare by people with narcolepsy across NHS settings may reflect diagnostic delay, comorbidities, and ongoing narcolepsy-related healthcare needs being met largely outside specialist sleep care, highlighting opportunities to improve healthcare services.
- Dual foundation models for accelerometry predict future health
Wrist accelerometers are ubiquitous and capture activity, sleep, and cardiorespiratory motion, but how this relates to future disease across the phenome is unclear. We encoded one week of UK Biobank accelerometry from 97,696 participants using two frozen self-supervised models and trained a multilabel survival model on these embeddings with participant age and sex for 390 outcomes. In 5,253 held-out participants, mean concordance was 0.688. A single component explained 76% of predicted risk variance and was associated with future disease burden and mortality. Nevertheless, disease-specific scores added discrimination beyond this shared axis for 85 of 101 well-powered outcomes. A higher-powered full-cohort out-of-fold analysis identified prodromal neurodegenerative signatures, strongest for Parkinson's disease (five-year time-dependent AUROC 0.90; 428 cases), with limited attenuation after lead-time washout. Daytime movement contributed most, whereas sleep-related and genetic information contributed selectively. These findings establish one week of wrist movement as a scalable, low-cost representation of future health for wearable-based risk assessment.
- Statistical Analysis Plan for the SImPLE Trial: A Study to test if illustrations and plain language ImProve cLinical trial Education
Background Traditional participant information and consent forms (PICFs) have changed little over time and are often lengthy and complex. A novel consent process incorporating plain language, an infographic brochure and a short explanatory video was developed to improve communication of clinical trial information. The SImPLE study was designed to evaluate whether this novel consent process improves comprehension of clinical trial information, participant engagement and the consent experience compared with a traditional PICF. Design and Setting SImPLE is a randomised two-period crossover study involving adults receiving cancer treatment who are potentially eligible for clinical trial participation. Study materials were developed for the ANZadapt (ANZUP2101) prostate cancer clinical trial; however, participants are not being recruited to ANZadapt itself. Participants are randomised to receive either a standard 17-page NHMRC-style PICF followed by a novel consent process, or the reverse sequence, with a washout period of at least 7 days between study periods. The novel consent process comprises a simplified 4-page PICF, infographic brochure and short explanatory video. Twenty-four hours following each PICF review, participants complete a comprehension assessment and structured interview. Outcomes and Endpoints The primary endpoint is comprehension of clinical trial information, measured using a study-specific 22-item questionnaire comprising 10 true/false and 12 multiple-choice questions. Secondary endpoints include acceptability, assessed through participant preference for communication format, and engagement, assessed through confidence in explaining the trial and likelihood of agreeing to participate. Planned Analyses The primary analysis will compare comprehension scores between the novel and standard consent approaches using a paired t-test among participants completing both study periods. Secondary outcomes relating to acceptability and engagement will be summarised descriptively and compared between consent approaches as appropriate. Sensitivity analyses will be performed to assess the robustness of the primary findings and the potential impact of crossover design effects.
- A Longitudinal Neuromelanin MRI Processing Framework Reduces Measurement Variability and Improves Precision in Parkinson's Disease
Background: Neuromelanin-MRI enables in vivo assessment of the substantia nigra (SN) and locus coeruleus (LC) in individuals with Parkinson's disease (PD), yet longitudinal studies rely on cross-sectional processing that may introduce measurement variability and confound estimates of change over time. Objectives: In this paper, a longitudinal neuromelanin-MRI processing framework is presented that is designed and validated to improve measurement stability and reduce processing-related variability across repeated scans. Methods: Imaging and clinical data from the Quebec Parkinson Network were analyzed in 268 participants (199 PD, 69 controls), including a longitudinal subset of 74 participants (49 PD, 25 controls) scanned approximately one year apart. Validation experiments evaluated slice-by-slice intensity normalization for slice dependent intensity variation, bias field correction for LC signal asymmetry, and the effects of longitudinal registration on measurement stability and PD-control discrimination. Results: Slice-by-slice intensity normalization significantly reduced brainstem intensity variability by 3.6%. A systematic leftward signal asymmetry was observed in the LC and persisted following N4 bias field correction, suggesting a scanner-related effect not captured by conventional bias field modeling. Longitudinal registration reduced annualized change variability by 25-36% for SN_CR and 27-34% for LC_CR metrics in controls, indicating improved within-subject measurement stability. Residual variability was also reduced for contrast-based metrics by up to 28%. Longitudinal registration generally produced larger PD-control effect sizes at baseline and follow-up, particularly for SN volume metrics. However, no significant method x group x time interactions were observed, indicating that estimated longitudinal trajectories did not differ significantly between longitudinal and conventional cross-sectional processing. Conclusions: Longitudinal registration reduced technical variability and improved the precision of NM-MRI measurements. Although it did not significantly enhance detection of longitudinal PD-control differences over the follow-up interval examined here, it provides a more robust framework for longitudinal NM-MRI studies and may improve sensitivity to subtler biological effects in future investigations.
- Ixodid Tick-Borne Pathogens as Candidate Triggers for Primary Sclerosing Cholangitis: Ecological Evidence
Background & Aims. Primary sclerosing cholangitis (PSC) is a cholestatic liver disease of unknown etiology whose prevalence varies >30-fold worldwide, peaking in Northern Europe and the U.S. Upper Midwest. This geographic distribution is not fully explained by recognized risk factors. We examine its correlation with Ixodes tick exposure. Approach & Results. PSC incidence across North America, Europe, and Oceania was compared with Lyme incidence, HLA-DRB1*03 frequency, latitude and other environmental factors. Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) were included as controls. A U.S. analysis (MarketScan, 2018-2022; 110.7 million person-years) correlated age and sex-standardized rates against 24 exposures, including Ixodes density and tick-borne infections, using ancestry-adjusted partial correlations. Cross-country PSC incidence tracked Lyme incidence (Spearman rho = 0.71-0.87); HLA-DRB1*03, AIH, and PBC did not. Alaska Native and Greenlandic populations, high-latitude but without established human exposure to Ixodes-borne pathogens, report no PSC despite high autoimmune liver disease and IBD. In the U.S., PSC was clustered and tracked Ixodes-borne pathogen incidence (ancestry-adjusted partial r, log scale: anaplasmosis +0.50, babesiosis +0.56, Powassan virus disease +0.52; in the Northeast-Midwest block, ancestry- and latitude-adjusted r = +0.72, +0.84, and +0.78, respectively). Non-Ixodes infections (Ehrlichia chaffeensis, spotted fever, tularemia), AIH, and PBC were null-to-negative; rural, agricultural, pollution, and healthcare-access also did not correlate. Conclusions. These ecological analyses are consistent with the hypothesis that Ixodes-borne pathogen exposure may trigger PSC. These ecological data cannot establish causation; they are hypothesis-generating, yielding falsifiable predictions for case control, serologic, and animal-model studies.
- Prevalence of Urogenital Schistosomiasis and Associated Factors in the Lac Region: A Focus on Environmental and Socioeconomic Contexts
Background: Urogenital schistosomiasis caused by Schistosoma haematobium remains a major public health concern in the Lake Chad region. This study aimed to estimate the cumulative prevalence of S. haematobium infection and to identify factors associated with test positivity within an intervention zone of the Ngouri health district, Lac Province, Chad. Methods: A cross-sectional analytical study was conducted using routinely collected data from the Dawa Mobile Health system between February 2024 and April 2025. A total of 4,504 individuals were included after data cleaning and biological consistency correction (22 haematuria cases recoded as positive). Bivariate analysis (Chi-square test) and multivariable logistic regression were performed. Results: The overall prevalence was 19.5% (95% CI: 18.4% - 20.7%). No statistically significant association was found for age (p=0.163), sex (p=0.939), marital status (p=0.858), occupation (p=0.704), or urine appearance in the binary model (p=0.116). Education level approached significance (p=0.078), with the highest prevalence observed at the primary level (23.0%). In multivariable analysis, only primary education was independently associated with positivity (adjusted OR=1.29, 95% CI: 1.06 - 1.57; p=0.011). Conclusion: Nearly one in five participants tested positive, confirming the high endemicity of the Ngouri district. The homogeneous distribution across demographic subgroups suggests widespread community exposure, supporting mass drug administration beyond school-aged children, strengthened WASH interventions, and consolidation of mobile health surveillance. Keywords: Schistosoma haematobium; urogenital schistosomiasis; prevalence; Lake Chad; Chad; mobile health; logistic regression.
- Anatomic and Physiologic Scoring is Associated with Mortality and Morbidity Following Operative Intervention for Adult Congenital Heart Disease Patients
BACKGROUND: The revised 2018 AHA/ACC guidelines introduced the Adult Congenital Heart Disease Anatomic and Physiologic classification (ACHD-AP) to better categorize disease severity and prognosis in the ACHD population. The ACHD-AP has not been rigorously studied as a perioperative prediction tool. OBJECTIVE: We aimed to assess the accuracy of the ACHD-AP classification in predicting perioperative morbidity and mortality. METHODS: This retrospective cohort study included 295 ACHD patients at a single academic institution between 2018 to 2022. Patients were identified by the STS congenital surgery registry and had undergone a congenital surgical procedure. The primary outcome was overall mortality. Secondary outcomes included short-term post-operative morbidity and comparison of the ACHD-AP score to other existing surgical mortality risk scores. Kaplan-Meier and area under the curve (AUC) of Receiver Operating Characteristic curves were used to evaluate mortality. Logistic regression was used to compare short-term morbidity. RESULTS: A total of 295 patients were included with a median age of 30 years (interquartile range 21-41 years) and 52% were female. There was a total of 14 deaths with 5 (2%) early post-operative deaths and 9 (3%) long-term deaths. By increasing anatomy complexity, overall mortality was 0%, 4% (n=10), and 8% (n=4), respectively. By increasing physiologic severity, overall mortality was 0%, 3% (n=2), 4% (n=7), and 14% (n=5). Moderate and complex anatomy trended towards increased mortality but were not statistically significant (p-value > 0.9). More severe physiology scores predicted increased mortality (p-value = 0.02). Higher physiologic or anatomic complexity scores were associated with longer post-operative length of stay (>5 days). The ACHD-AP AUC was 0.711 for mortality, which was comparable to the Adult Congenital Heart Surgery (ACHS) score (AUC 0.798) and better than the PEACH score (AUC 0.575). CONCLUSION: The ACHD-AP score revealed comparable or better predictive power to existing risk models. Worsening physiologic and anatomy scores were associated with worse post-operative outcomes. Further prospective studies are needed to validate the ACHD-AP score as a prognostic factor for patients undergoing ACHD surgery.
- Who regulates AI when Washington won’t?
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- Association Between Out-of-Hospital Falls and Cardiovascular Events in Patients with Coronary Heart Disease: A Retrospective Cohort Study
Background Falls are increasingly recognized as adverse events in coronary heart disease (CHD) patients, yet their prognostic implications remain incompletely understood. This study examined the independent associations of falls with mortality and major adverse cardiovascular events, and the roles of functional status and frailty in these relationships. Methods This retrospective cohort study enrolled 2,139 CHD patients with median follow-up of 36 months. Falls were ascertained via telephone interviews every 3 months. Primary outcomes included major adverse cardiovascular events (MACE) and major adverse cardiovascular and cerebrovascular events (MACCE). Secondary outcomes comprised all-cause and cardiac mortality. Multivariable Cox models with stepwise adjustment for functional status indicators were constructed, with subgroup analyses stratified by frailty status. Results During follow-up, 171 patients (8.0%) experienced falls. Falls were associated with mortality in univariate analysis but not after adjusting for functional status, indicating mediation by functional decline. In contrast, falls remained independently associated with MACE (HR=1.73, 95%CI: 1.17-2.57, P=0.006) and MACCE (HR=1.67, 95%CI: 1.14-2.46, P=0.009) in fully adjusted models. Frailty significantly modified this association (P for interaction <0.001). Among robust patients, falls conferred substantially elevated risk (MACE: HR=4.08, 95%CI: 2.37-7.01; MACCE: HR=3.94, 95%CI: 2.30-6.76), whereas no significant association was observed in pre-frail or frail patients. Conclusions Falls independently predict long-term MACE and MACCE in CHD patients, with mortality effects mediated by functional status. Frailty significantly modifies the fall-cardiovascular event relationship--robust patients experiencing falls face substantially elevated cardiovascular risk and warrant comprehensive evaluation. These findings support integrating fall history into cardiovascular risk assessment and implementing frailty-stratified management.
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- Pitt leads AI‑quantum project in DOE’s Genesis Mission
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- Trump is loosening AI guardrails. What does that mean for you?
Trump is loosening AI guardrails. What does that mean for you? azcentral.com and The Arizona Republic
- Cheaper, open and intelligent: Chinese AI models gain ground, as they make inroads in the US
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- ChainBow Releases Otoha, an iOS and macOS Audio Player With Automatic Subtitle Generation
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- New AI Tools Let Readers Talk To Books
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- Inspired by how children learn, new AI framework learns to theorize the world from observations
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- AI underwater robots can now track diver stress via exhaled bubbles
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- Can AI’s power problem become a clean-energy opportunity?
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- ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding
Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with...
- KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability
Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In clinical workflows, chest X-ray classifiers are increasingly paired with Vision-Language Models (VLMs) to generate natural-language explanations. Howeve...
- The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation
Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear. Existing models are trained on uncontrollable and opaque Internet data, making it difficult to identify how planning ability is acquired, shaped, and integrated. To address ...
- DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data
Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixed processing strategy at the corpus or domain level and apply it uniformly to many examples, without adapting to the needs of each example. We propose...
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- Efficient LLM-Generated Shuttling Compilers for Complex Trapped-Ion Architectures
Trapped-ion quantum computers rely on shuttling compilers, which cast an input algorithm into a sequence of ion-qubit movements within a given architecture. We present the first study in which a single frontier large language model (LLM), Claude Opus 4.7, generates and iteratively refines the full P...
- Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification
Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance. However, real-world scenarios subject to operational constraints, such as sensor failures or privacy restrictions, lead to inconsistent modality availability between training...
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- Eviction as Estimation: A Fixed-Lag Smoothing View of Test-Time Memory, and When Measuring Beats Accumulating
A language model with a bounded working memory must repeatedly decide which stored items to keep. Every deployed method decides the moment an item arrives, from the past (StreamingLLM, H2O) or from a guess about the future (SnapKV). We recast the choice as an estimation problem on a hidden signal, w...
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- Reason-Mediated Behavioral Models for Auditing LLM Social Simulators
Large language models are increasingly used as social simulators, including as synthetic survey respondents. Most evaluations ask whether simulated outcomes resemble human outcomes. We argue that this is necessary but too weak: a simulator can match the final answer while using the wrong rationale-d...
- Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents
Autonomous LLM agents processing mixed-confidentiality data face severe security risks from prompt injection attacks and reasoning errors. While dynamic Information Flow Control (IFC) provides structural security guarantees, traditional taint tracking permanently taints an agent's context upon readi...
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- Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review
Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to assess the validity of LLM-generated reviews, making it difficult to gauge how much trust to place in them. The role of ...
- Artificial Intelligence and Innovation Ecosystem: Evolutionary Developments, Challenges, and Future Directions
The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. The rise of Artificial Intelligence (AI) has significantly accelerated the global processes of digitization, informatization, and intelligence. Explo...
- Tag Questions and the Generational Reversal of Sycophancy Across 45 Language Models
Appending a two-word confirmation tag to a decision question -- "Is X the better choice?" versus "X is the better choice, right?" -- changes whether a language model endorses the choice. We measure this tag effect on 20 frozen, ground-truth-free decisions between two defensible options, counterbalan...
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