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Резюме, представленные на 32nd Ежегодная конференция Международного общества по изучению качества жизни.

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Intelligence Architectures and Machine Learning Applications in Contemporary Spine Care.

The rapid evolution of artificial intelligence (AI) and machine learning (ML) technologies has initiated a paradigm shift in contemporary spine care. This narrative review synthesizes advances across imaging-based diagnostics, surgical planning, genomic risk stratification, and post-operative outcome prediction. We critically assess high-performing AI tools, such as convolutional neural networks for vertebral fracture detection, robotic guidance platforms like Mazor X and ExcelsiusGPS, and deep learning-based morphometric analysis systems. In parallel, we examine the emergence of ambient clini

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… Large language models (LLMs) and Natural Language Processing-driven (NLP-driven) tools are beginning to automate the creation of radiology reports from spine imaging data. Many current systems combine image analysis (e.g., segmentation, detection, measurements) with templated language output. … Importantly, integrating GWAS signals with phenotypic features using machine learning models, where genomic data are fused with radiomics and clinician notes parsed by large language models, has improved prediction of early neurological deterioration and postoperative sepsis in ASD cohorts, enabling …

Screening for comprehensive social needs in patients with cancer: a narrative review.

BackgroundPatients with cancer who report social needs have worse quality of life, lower health-care access, and suboptimal health outcomes. However, screening for social needs does not happen systematically, and successful screening tools, strategies, and workflows have seldom been described. The downstream effects of screening including resource navigation have also not been well characterized. The objective of this narrative review was to fill these gaps.MethodsTwo investigators searched PubMed and Embase for studies that implemented a patient-facing social screening tool among patients wit

2021 International Cancer Education Conference Program and Abstracts.

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Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases

Background/Objectives: Although the Spinal Instability Neoplastic Score (SINS) is widely used to estimate spinal metastases fracture risk and guide decisions on stabilisation procedures, prior studies have demonstrated mixed results. Patients with the same score exhibit clinically heterogeneous outcomes, with some SINS criteria correlating less well with the estimated fracture risk than others. There are also barriers to implementation such as the time burden required for manual calculation and interobserver variability associated with qualitative morphological criteria. SINS also lacks sensit

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… To address these constraints, recent efforts have focused on integrating artificial intelligence, including large language models (LLMs), to automate the scoring process [ 22 , 23 ]. … Evaluating the Accuracy of Privacy-Preserving Large Language Models in Calculating the Spinal Instability Neoplastic Score (SINS) Cancers 2025 17 2073 10.3390/cancers17132073 40647373 PMC12248813 24. Ehresman J. Schilling A. Yang X. Pennington Z. Ahmed A.K. Cottrill E. Lubelski D. Khan M. …

Knowledge-map and bibliometric analysis of scientific research on FDA-approved Chimeric Antigen Receptor T cell products (2015-2024).

BackgroundChimeric Antigen Receptor T cell (CAR-T) therapy is a groundbreaking, personalized immunotherapy that genetically engineers patient or donor-derived T cells to recognize and eliminate cancer cells. The U.S FDA has approved six CAR-T cell products in the past decade.ObjectiveGiven their clinical success and scientific novelty, this study aimed to map the research landscape surrounding the FDA-approved CAR-T cell therapies using bibliometric and knowledge mapping analysis.MethodsA comprehensive title/abstract search was conducted in Scopus database for documents published between 2015

Insight and Recommendations for Fragile X-Premutation-Associated Conditions from the Fifth International Conference on FMR1 Premutation.

The premutation of the fragile X messenger ribonucleoprotein 1 (FMR1) gene is characterized by an expansion of the CGG trinucleotide repeats (55 to 200 CGGs) in the 5' untranslated region and increased levels of FMR1 mRNA. Molecular mechanisms leading to fragile X-premutation-associated conditions (FXPAC) include cotranscriptional R-loop formations, FMR1 mRNA toxicity through both RNA gelation into nuclear foci and sequestration of various CGG-repeat-binding proteins, and the repeat-associated non-AUG (RAN)-initiated translation of potentially toxic proteins. Such molecular mechanisms contribu

Применение искусственного интеллекта в перипостетической суставной инфекции.

Перипростетическая суставная инфекция (ПСО) представляет собой one Из наиболее разрушительных осложнений, вызванных общей совместной артропластикой, часто требующих дополнительных операций и антимикробной терапии, и потенциально ведущих к инвалидности. Это значительно увеличивает нагрузку как на пациентов, так и на систему здравоохранения. С учетом значительных страданий, причиняемых ПСО, его профилактика и лечение уже давно являются ключевыми факторами, вызывающими озабоченность. Вместе с тем сохраняются проблемы, связанные с точной оценкой индивидуального риска, предотвращением инфекции, сов

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… PJI patient education Large language models (LLMs) like ChatGPT are rapidly emerging as powerful tools in the medical field. …

Evaluation of controlled vocabulary resources for development of a consumer entry vocabulary for diabetes.

BackgroundDigital information technology can facilitate informed decision making by individuals regarding their personal health care. The digital divide separates those who do and those who do not have access to or otherwise make use of digital information. To close the digital divide, health care communications research must address a fundamental issue, the consumer vocabulary problem: consumers of health care, at least those who are laypersons, are not always familiar with the professional vocabulary and concepts used by providers of health care and by providers of health care information, a

Development of a clinical trial knowledge management application for community oncology.

IntroductionParticipation in cancer clinical trials is low in community oncology settings, partly because institution-specific trial information is fragmented. We evaluated feasibility of embedding curated trial content in an AI-enabled knowledge management application.Materials and methodsAt a regional community oncology network, coordinators and disease teams compiled actively recruiting trials. Core elements (title, conditions, biomarkers, stage/line, and recruiting status) were structured for point-of-care display and uploaded. AI-assisted extraction generated protocol summaries and eligib

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… Performance of retrieval-augmented large language models to recommend head and neck cancer clinical trials . J Med Internet Res. 2024 ; 26 : e60695 . 39405514 10.2196/60695 PMC11522650 22 Pfiffner PB , Oh J , Miller TA , Mandl KD. … Accuracy of large language models for matching cancer patients to biomarker-driven clinical trials based on molecular profiles . …

Italian onco-haematological patients' preferences in bad news communication: a preliminary investigation.

BackgroundThe manner in which bad news is communicated in oncological contexts can affect patients' engagement, their coping strategies and therapeutic compliance. Although this topic has been broadly investigated since the nineties, to the best of our knowledge, little has been written about Italian patients' experiences and preferences concerning what the oncologists should disclose and how they should intimate patients about their health conditions in different stages of oncological disease.MethodsIn an attempt to fill this gap, an online self-report questionnaire was administered to a samp

Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset.

The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fairness, and biases in healthcare scenarios where human lives are at stake call for a careful and thorough examination of both datasets and models. In this work, we focus on MIMIC-IV (Medical Information Mart for Intensive Care, version IV), the largest publicly available healthcare dataset, and conduct comprehensive analyses of interpretability as w

:: 8th Европейский конгресс фармацевтики: выдержки из выступлений

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… Artificial Intelligence, using large language models (LLM) and real-world evidence as well as big data are now integrated in the regulatory decision-making process. More developments are expected in 2025 and beyond. … Bridging the gap in drug safety data analysis: Large Language Models for SQL query generation. 2024, arXiv preprint arXiv:2406.10690. 3. Painter JL, Mahaux O, Vanini M, et al. Enhancing drug safety documentation search capabilities with Large Language Models: a user-centric approach. …

Machine Learning for Multi-Omics Characterization of Blood Cancers: A Systematic Review.

Artificial Intelligence and machine learning are increasingly used to interrogate complex biological data. This systematic review evaluates their application to multi-omics for the molecular characterization of hematological malignancies, an area with unmet clinical need. We searched PubMed, Embase, Institute of Electrical and Electronics Engineers Xplore, and Web of Science from January 2015 to December 2024. Two reviewers screened records, extracted data, and used a modified appraisal emphasizing explainability, performance, reproducibility, and ethics. From 2847 records, 89 studies met incl

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… There has recently been increased use of Natural Language Processing (NLP) and ML in the interrogation of scientific text to generate large language models (LLMs) [ 69 , 70 ]. … Foundation models, including large language models trained on molecular data, show promise for generalized molecular understanding. …

Качественное изучение преференций в области физических упражнений среди испаноязычных взрослых с множественным склерозом.

Цель этого исследования состояла в том, чтобы определить компоненты идеальной программы тренировки для испаноязычных лиц с множественным склерозом (МС), культурными изменениями и способами распространения информации среди этой группы населения. В онлайновом режиме были проведены полуструктурированные собеседования с 27 взрослыми людьми, которые, как было установлено, являются испаноязычными. Для оценки необходимых и желаемых компонентов программы учений использовался подход, основанный на дедуктивном анализе содержания. Участники высказали предпочтения в отношении "что", "когда", "где" и "кто"

Approach to the Patient With Bone Fracture: Making the First Fracture the Last.

The global burden of osteoporosis and osteoporotic fractures will increase significantly as we enter a rapidly aging population. Osteoporotic fractures lead to increased morbidity, mortality, and risk of subsequent fractures if left untreated. However, studies have shown that the majority of patients who suffer an osteoporotic fracture are not investigated or treated for osteoporosis, leading to an inexcusable "osteoporosis care gap." Systematic and coordinated models of care in secondary fracture prevention known as fracture liaison services (FLS) have been established to streamline and impro

PROMIS® Health Organization (PHO) 2021 Conference Abstracts.

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Psychometric properties and clinical utility of the EORTC QLQ-BM22 in patients with bone metastases: a systematic review.

BackgroundThe European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire for bone metastases 22 (EORTC QLQ-BM22) is a site-specific health-related quality-of-life instrument for patients with bone metastases. However, modern treatments and extended survivorship have introduced new toxicity profiles and clinical challenges. We systematically assessed the measurement performance of QLQ-BM22 to determine if contemporary evidence supports updating the module.MethodsA search was conducted using Medline, Embase, and Cochrane Central Register of Controlled Trials from in

Prevalence of pain and its association with symptoms of post-traumatic stress disorder, depression, anxiety and distress in 846 cancer patients: A cross sectional study.

ObjectivePain depicts a severe physical symptom but its relationship to mental health problems is not well studied in cancer patients. The aim of this study was to investigate the prevalence of pain and its correlation with symptoms of post-traumatic stress disorder (PTSD), depression, anxiety and psychological distress in a large sample of cancer patients.MethodsFrom 2010 to 2019, cancer patients who received outpatient treatment at the Medical University of Vienna were assessed with the Post-Traumatic Symptom Scale (PTSS-10) and the Hospital Anxiety and Depression Scales. A visual analogue s

Genetic Syndromes, Maternal Diseases and Antenatal Factors Associated with Autism Spectrum Disorders (ASD).

Autism spectrum disorder (ASD) affecting about 1% of all children is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal, and postnatal etiologies. In addition, ASD is often an important clinical presentation of some well-known genetic syndromes in human. We discuss these syndromes as well as the role of the more important prenatal factors affecting the fetus throughout pregnancy which may also be associated with ASD. Among the genetic disorders we find Fragile X, Rett syndrome, tuberous sclerosis, Timothy syndrome, Phelan-McDermid syndrome, Hamartoma tumo