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Advance directives in Finnish long-term care: Do sociodemographic characteristics and regional factors matter?

BackgroundAdvance directives (AD) help ensure quality end-of-life care by preventing inappropriate or unwanted treatments. This is particularly important for older people in long-term care (LTC).AimsThis study examines sociodemographic and regional factors associated with the presence of ADs among Finnish round-the-clock LTC residents.MethodsThis retrospective register study included 6,090 Finnish round-the-clock LTC residents aged ⩾65 years who died of chronic progressive diseases in 2019 and had undergone a comprehensive evaluation of health status and care needs using a standardized, intern

Унификация одиссеи: искусственный интеллект для диагностирования и лечения редких заболеваний.

Подытожить текущие проблемы в диагностике и лечении редких заболеваний (РД), осветить последние достижения в области искусственного интеллекта (АИ) для РД и предложить модель будущего состояния лечения пациентов РД. Многодисциплинарный экспертный обзор с кратким изложением современных практических задач и мер по ограничению ставок в области РД-клиентов с учетом ключевых клинических и исследовательских соображений в отношении нормативных и экономических ограничений. 10,000 известные РД оказывают коллективное воздействие 1 В 10 Американцы, в целом 30 million Люди. Ежегодно на РД приходится свыше

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… Enhancing the accuracy of human phenotype ontology identification: comparative evaluation of multimodal large Language models . J Med Internet Res . 2025 ; 27 : e73233 . 10.2196/73233 . 40456109 PMC12148245 37. … Large Language models with Temporal reasoning for longitudinal clinical summarization and prediction . Find ACL EMNLP . 2025 ; 2025 : 20715 – 35 . 10.18653/v1/2025.findings-emnlp.1128 . 41399802 PMC12702291 44. …

The role of AI in oncology: present applications and future horizons.

Artificial intelligence (AI) offers a powerful means to accelerate precision oncology by individualizing care in an era of rapidly evolving treatment paradigms. However, there is limited regulatory oversights for safe clinical implementation of AI, and concerns surrounding data bias, ownership, and privacy have hindered broad integration into healthcare practice. In this perspective, we offer a forward-looking roadmap for the dissemination of AI in oncology. We discuss the role for AI in guiding biomarker-driven patient selection for clinical trials and in facilitating both personalized drug s

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… Matching patients to clinical trials with large language models. Nat. Commun. 15 , 9074 (2024). 10.1038/s41467-024-53081-z PMC11574183 39557832 11. … PRISM: Patient Records Interpretation for Semantic Clinical Trial Matching system using large language models. npj Digit. Med. 7 , 305 (2024). 10.1038/s41746-024-01274-7 PMC11519882 39468259 18. …

Survival outcomes and healthcare utilization between immigrant patients and Danish-born patients with hematological cancers: a Danish population-based study.

Overall survival (OS) for patients with a hematological cancer may differ between immigrant and Danish-born patients due to disparities in socioeconomic status, health literacy, and language proficiency. This cohort study aimed to investigate survival and hospitalization according to immigrant status while controlling for confounders. Patients with newly diagnosed hematological cancer in 2000-2020 were identified in the Danish nationwide hematological registers and stratified into Danish-born, Western, and non-Western patients. Patients were followed from diagnosis until death, 31st December 2

Public Omics Explorer (POE): Создание возможностей для комплексного семантического поиска по наборам данных GEO omics на основе публикаций PubMed.

Экспоненциальный рост общедоступных массивов данных об омиках и биомедицинской литературы создает как возможности, так и проблемы для открытия данных в области биологических наук. В то время как " Gene Express Omnibus " (GEO) содержит миллионы высокопроизводительных экспериментальных наборов данных, Европейский архив нуклеотидов (ENA) хранит соответствующие исходные данные о последовательности, а " PubMed " содержит большой объем соответствующих научных публикаций, комплексное исследование этих ресурсов по-прежнему носит ограниченный характер. Мы представляем "Public Omics

Precision Medicine Through Network Language: Integrating Clinical Insight and Data Expertise.

Precision medicine is facing a critical transition driven by the growing complexity of biological data and the insufficient ability of current models to translate such data into clinically meaningful information. Linear, single-gene approaches are no longer adequate to explain the multifactorial nature of most modern diseases, whose phenotypes emerge from combinations of genetic, molecular, and environmental factors. Network-based precision medicine addresses this by providing a systemic framework capable of integrating heterogeneous omics data, interactomes, and clinical information to identi

Поощрение использования продольных электронных медицинских записей: обучение по изучению реальных мировых данных о последствиях хронических заболеваний.

Для борьбы с хроническими заболеваниями требуется постоянный мониторинг деятельности по борьбе с заболеваниями и терапевтическое реагирование в целях оптимизации планов лечения. С учетом растущей доступности методов лечения, позволяющих сглаживать заболевания, крайне важно изучить вопрос о сравнительной эффективности и долгосрочных результатах, помимо тех, которые могут быть получены в ходе выборочных клинических испытаний. Мы внедряем всеобъемлющий трубопровод для получения воспроизводимых и обобщенных реальных данных о результатах болезней за счет использования электронных данных о состоянии

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… The embedding vectors can be obtained from pre-trained embeddings, such as those powering the ONCE search engine, or by embedding the textual descriptions of the features using large language models such as Clinical BioBERT [ 31 ], CODER [ 32 ], BGE [ 33 ], or even GPT-4 [ 34 ]. … Large language model–based AI systems can play a transformative role by extracting structured information from clinical notes. …

A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study.

BackgroundThe identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve the quality of life of patients with cancer. Artificial intelligence can aid in the extraction of objective pain biomarkers for patients with cancer with bone metastases (BMs).ObjectiveThis study aimed to develop and evaluate a scalable natural language processing (NLP)- and radiomics-based machine learning pipeline to differentiate between painless and painful BM lesions in simulation computed tomo

Ручная обработка против методов извлечения глубоких признаков для диагностики множественной скlerоза на основе МРТ.

Фон: Несмотря на значительные продвижения в анализе медицинских изображений, автоматический диагноз множественной скlerоза (МС) на основе магнитно-резонансной томографии (МРТ) остается сложной задачей из-за сложности 3D-данных мозга и вариабельности вида плоскостей поражений. Цель: В этой работе мы предлагаем эффективную и оптимизированную систему извлечения признаков для автоматического диагноза МС с использованием МРТ с весом FLAIR, T1 и T2. Предложенный подход улучшает Декимальные Дескрипторные Паттерны (DDP) за счет интеграции локальной информации градиента, создавая 3D-представление текст

What factors influence patient participation in an artificial intelligence-based initiative to optimise referrals from primary to specialist haematology care? A multicentre retrospective observational study in four Spanish hospitals.

ObjectivesIncreasing demand for haematological specialist care makes the optimisation of referrals and outpatient workflow a priority. Automated placing of standardised test orders prior to the first appointment may provide haematologists with necessary information to reach diagnoses and initiate treatment at the first patient encounter, reducing low-value follow-up appointments. We aimed to evaluate rates of patient participation in an initiative using artificial intelligence to place standardised test orders as well as reasons for non-participation, differences in the number of participants

The Success of Cancer Crowdfunding Campaigns: Project and Text Analysis.

BackgroundRecent studies have analyzed the factors that contribute to variations in the success of crowdfunding campaigns for a specific cancer type; however, little is known about the influential factors among crowdfunding campaigns for multiple cancers.ObjectiveThe purpose of this study was to examine the relationship between project features and the success of cancer crowdfunding campaigns and to determine whether text features affect campaign success for various cancers.MethodsUsing cancer-related crowdfunding projects on the GoFundMe website, we transformed textual descriptions from the c

Willingness and concerns of transfusion-dependent hematological patients toward the option of home transfusion therapy.

BackgroundOne of the main obstacles of providing home-based palliative care to transfusion-dependent hematology patients is the lack of home transfusions services. While healthcare professionals are concerned with safety and cost of home transfusions, the attitude of the patients toward home transfusions are mostly unknown.AimTo obtain quantitative data regarding the willingness and concerns of transfusion-dependent patients with hematological diseases toward the option of home transfusions.DesignA cross sectional survey including a self-administered questionnaire in one of the three main spok

Decoding Immunodeficiencies with Artificial Intelligence: A New Era of Precision Medicine.

Primary and secondary immunodeficiencies comprise a wide array of illnesses marked by immune system abnormalities, resulting in heightened vulnerability to infections, autoimmunity, and cancers. Notwithstanding progress in diagnostic instruments and an enhanced comprehension of the underlying pathophysiology, delayed diagnosis and underreporting persist as considerable obstacles. The implementation of artificial intelligence into clinical practice has surfaced as a viable method to enhance early detection, risk assessment, and management of immunodeficiencies. Recent advancements illustrate ho

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… Another study proposed that large language models (LLMs) could assist clinical immunologists by providing valuable recommendations for the diagnosis and management of PIs [ 48 ]. … Exploring the potential of lightweight large language models for AI-based mental health counselling task: A novel comparative study Sci. Rep. 2025 15 22463 10.1038/s41598-025-05012-1 40596002 PMC12214774 111. Orange J.S. Seeborg F.O. Boyle M. Scalchunes C. Hernandez-Trujillo V. …

Sex differences in physical activity, psychosocial determinants, and symptom outcomes in knee osteoarthritis: a cross-sectional analysis of a Hispanic/Latino-predominant cohort.

Knee osteoarthritis (KOA) is a chronic disease that often leads to persistent pain, functional limitations, and diminished quality of life. Physical activity can be an effective countermeasure but its adherence typically relies on behavioral determinants. Currently, there is limited work investigating how clinical symptoms among patients with KOA affect behavioral determinants, and there is a need for further insight into why females engage in less physical activity. The purpose of this study was to investigate these questions in a sample of patients with KOA. Patients (n = 736; mean age 56.4

Computational proteomics to enhance personalized treatment of COVID-19 and Long COVID.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to significant global health burden, including both acute infections and persistent post-acute sequelae, also known as Long COVID (LC) in survivors. While clinical management has reduced case-fatality rates, a substantial proportion of patients develop LC, a heterogeneous syndrome with long-term symptoms. This complex continuum requires therapeutic strategies for both the acute and chronic phases. Plasma proteomics has emerged as a powerful tool in precision medicin

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… Large language models (LLMs) have demonstrated how integrating massive, heterogeneous datasets into unified architectures can unlock powerful downstream applications. … General-purpose large language models (LLMs) have been used for biomedical literature mining, clinical note extraction, and hypothesis generation by processing unstructured text alongside structured omics data. …

Psychometric evaluation of Oral Mucositis Daily Questionnaire: A cross-cultural adaptation of the Malay version in multiethnic adult autologous stem cell transplant.

ObjectiveMucositis is one of the most feared side effects of cancer treatment. Psychometric analysis of a patient self-assessment score, the oral mucositis daily questionnaire in Malay (OMDQ-Mal) and its construct validity by means of confirmatory factor analysis (CFA) is lacking. This research aimed to test the validity and reliability of OMDQ-Mal.MethodsA total of 114 autologous stem-cell transplantation patients aged ≥ 18 years old at a national hematology center in Malaysia from April 2019 to December 2020 completed OMDQ-Mal concurrently with physician scores. Internal consistency and repr

Natural language processing for abstraction of cancer treatment toxicities: accuracy versus human experts.

ObjectivesExpert abstraction of acute toxicities is critical in oncology research but is labor-intensive and variable. We assessed the accuracy of a natural language processing (NLP) pipeline to extract symptoms from clinical notes compared to physicians.Materials and methodsTwo independent reviewers identified present and negated National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v5.0 symptoms from 100 randomly selected notes for on-treatment visits during radiation therapy with adjudication by a third reviewer. A NLP pipeline based on Apache clinical Text Analys

Longitudinal Cognitive Assessment After CAR-T Cell Immunotherapy: A Prospective Cohort Study.

(1) Background: Cognitive dysfunction represents an emerging concern in chimeric antigen receptor T-cell (CAR-T) therapy recipients, yet longitudinal data using simple, clinically applicable tools are lacking. (2) Methods: We conducted a single-center prospective cohort study of consecutive adults with hematologic malignancies treated with commercially available CAR-T cell products between May 2023 and November 2025 at our center. Cognitive function was evaluated with the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) at baseline (before the administration of lym

Коммуникационные трудности и связи с грамотностью в области здравоохранения, медикаментозными представлениями и привитием многоразового склероза.

ВВЕДЕНИЕ: Трудности в области коммуникации являются распространенной, но недостаточно признанной чертой множественного склероза (МС) и могут влиять на качество жизни, участие в жизни общества и участие в здравоохранении. О том, в какой степени деятельность в области коммуникации связана с медицинской грамотностью, верованиями в медикаментозные средства и приверженностью НР, по-прежнему плохо известно. МЕТОДЫ: Это перекрестное исследование охватывало 307 взрослых, которые были набраны в госпитале Аль-Башир в Аммане, Иордания. Участники заполнили проверенные варианты вопросника по коммуникационн

Artificial intelligence powers regenerative medicine into predictive realm.

The expanding regenerative medicine toolkit is reaching a record number of lives. There is a pressing need to enhance the precision, efficiency, and effectiveness of regenerative approaches and achieve reliable outcomes. While regenerative medicine has relied on an empiric paradigm, availability of big data along with advances in informatics and artificial intelligence offer the opportunity to inform the next generation of regenerative sciences along the discovery, translation, and application pathway. Artificial intelligence can streamline discovery and development of optimized biotherapeutic

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… Caution is necessary as large language models may influence medical knowledge, with risk for misuse and important downstream ramifications [ 84 ]. … Poisoning medical knowledge using large language models . Nat Mach Intel . 2024 ; 6 ( 10 ): 1156 – 1168 . 85. Goetz L , Seedat N , Vandersluis R , et al . Generalization-a key challenge for responsible AI in patient-facing clinical applications . …