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"Dimitri, Simona"
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Dialogical AI for Cognitive Bias Mitigation in Medical Diagnosis
Large Language Models (LLMs) promise to enhance clinical decision-making, yet empirical studies reveal a paradox: physician performance with LLM assistance shows minimal improvement or even deterioration. This failure stems from an “acquiescence problem”: current LLMs passively confirm rather than challenge clinicians’ hypotheses, reinforcing cognitive biases such as anchoring and premature closure. To address these limitations, we propose a Dialogic Reasoning Framework that operationalizes Dialogical AI principles through a prototype implementation named “Diagnostic Dialogue” (DiDi). This framework operationalizes LLMs into three user-controlled roles: the Framework Coach (guiding structured reasoning), the Socratic Guide (asking probing questions), and the Red Team Partner (presenting evidence-based alternatives). Built upon Retrieval-Augmented Generation (RAG) architecture for factual grounding and traceability, this framework transforms LLMs from passive information providers into active reasoning partners that systematically mitigate cognitive bias. We evaluate the feasibility and qualitative impact of this framework through a pilot study (DiDi) deployed at Centro Chirurgico Toscano (CCT). Through purposive sampling of complex clinical scenarios, we present comparative case studies illustrating how the dialogic approach generates necessary cognitive friction to overcome acquiescence observed in standard LLM interactions. While rigorous clinical validation through randomized controlled trials remains necessary, this work establishes a methodological foundation for designing LLM-based clinical decision support systems that genuinely augment human clinical reasoning.
Journal Article
Effects of coenzyme Q10 on statin-induced myopathy: a meta-analysis of randomized controlled trials
To evaluate the efficacy of coenzyme Q10 (CoQ10) supplementation on statin-induced myopathy.
We searched the MEDLINE, Cochrane Library, Scopus, and EMBASE databases (November 1, 1987, to May 1, 2014) to identify randomized controlled trials investigating the impact of CoQ10 on muscle pain and plasma creatine kinase (CK) activity as 2 measures of statin-induced myalgia. Two independent reviewers extracted data on study characteristics, methods, and outcomes.
We included 6 studies with 302 patients receiving statin therapy: 5 studies with 226 participants evaluated the effect of CoQ10 supplementation on plasma CK activity, and 5 studies (4 used in the CK analysis and 1 other study) with 253 participants were included to assess the effect of CoQ10 supplementation on muscle pain. Compared with the control group, plasma CK activity was increased after CoQ10 supplementation, but this change was not significant (mean difference, 11.69 U/L [to convert to μkat/L, multiply by 0.0167]; 95% CI, -14.25 to 37.63 U/L; P=.38). Likewise, CoQ10 supplementation had no significant effect on muscle pain despite a trend toward a decrease (standardized mean difference, -0.53; 95% CI, -1.33 to 0.28; P=.20). No dose-effect association between changes in plasma CK activity (slope, -0.001; 95% CI, -0.004 to 0.001; P=.33) or in the indices of muscle pain (slope, 0.002; 95% CI, -0.005 to 0.010; P=.67) and administered doses of CoQ10 were observed.
The results of this meta-analysis of available randomized controlled trials do not suggest any significant benefit of CoQ10 supplementation in improving statin-induced myopathy. Larger, well-designed trials are necessary to confirm the findings from this meta-analysis.
Journal Article
عالم الديناصورات
هذا الكتاب مخصص للأطفال يستهدف الطفولة المبكرة وتعمل علي اسثمار الطفل في بناء المهارات المختلفة المرتبطة بالخيال والأبتكار وقوة الشخصية والبحث عن حلول إبداعية ويستمد الطفل الكثير من العلم والمعرفة والمعلومات من المنهج السلوكي التربوي رائع يعلم الطفل كيف يستخلص من مشكلاته وكيف يبني شخصيته بشكل مميز ويعطي المربي حلولا لحل مشكلات أبنه تعنيه عن تجاوز الأزمة وإنهائها.
BOOK
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.
To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms.
In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016.
Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated.
Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity.
While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation.
Journal Article
الليل
هذا الكتاب مخصص للأطفال يستهدف الطفولة المبكرة وتعمل علي اسثمار الطفل في بناء المهارات المختلفة المرتبطة بالخيال والأبتكار وقوة الشخصية والبحث عن حلول إبداعية ويستمد الطفل الكثير من العلم والمعرفة والمعلومات من المنهج السلوكي التربوي رائع يعلم الطفل كيف يستخلص من مشكلاته وكيف يبني شخصيته بشكل مميز ويعطي المربي حلولا لحل مشكلات أبنه تعنيه عن تجاوز الأزمة وإنهائها.
BOOK
AMPA receptor GluA2 subunit defects are a cause of neurodevelopmental disorders
AMPA receptors (AMPARs) are tetrameric ligand-gated channels made up of combinations of GluA1-4 subunits encoded by
GRIA1-4
genes. GluA2 has an especially important role because, following post-transcriptional editing at the Q607 site, it renders heteromultimeric AMPARs Ca
2+
-impermeable, with a linear relationship between current and trans-membrane voltage. Here, we report heterozygous
de novo GRIA2
mutations in 28 unrelated patients with intellectual disability (ID) and neurodevelopmental abnormalities including autism spectrum disorder (ASD), Rett syndrome-like features, and seizures or developmental epileptic encephalopathy (DEE). In functional expression studies, mutations lead to a decrease in agonist-evoked current mediated by mutant subunits compared to wild-type channels. When GluA2 subunits are co-expressed with GluA1, most
GRIA2
mutations cause a decreased current amplitude and some also affect voltage rectification. Our results show that
de-novo
variants in
GRIA2
can cause neurodevelopmental disorders, complementing evidence that other genetic causes of ID, ASD and DEE also disrupt glutamatergic synaptic transmission.
Genetic variants in ionotropic glutamate receptors have been implicated in neurodevelopmental disorders. Here, the authors report heterozygous
de novo
mutations in the
GRIA2
gene in 28 individuals with intellectual disability and neurodevelopmental abnormalities associated with reduced Ca
2+
transport and AMPAR currents.”
Journal Article
A ten‐year follow‐up of the prevalence of pressure injuries in the Czech Republic: Analysis of the National Registry
The study aims to follow up on the analysis of Pressure injuries (PIs) prevalence conducted between 2007 and 2014 and after the new methodological requirements for PIs surveillance establishment at the national level. A retrospective, nationwide cross‐sectional analysis of data regarding the STROBE checklist was collected by the National Health Information System (NHIS). The International Classification of Diseases (ICD‐10) diagnoses L89.0‐L89.9 for PIs were used in the period 2010–2019. A total of 264 442 records of patients with diagnoses of L89.0‐L89.9 were identified from 2010 to 2019 (26 444 patients per year on average). The numbers are increasing every year, and there is a 40% increase between 2010 and 2019. When comparing recorded PIs, the percentage of PIs occurrence in category I decreased, and the number of PIs in category IV increased in the second analysed period. Still, in absolute numbers, there is an increase across all categories. The age of patients with recorded PIs also rose slightly in the second analysed period. We have proven the PIs prevalence increase in an ageing population.
Journal Article
