Опубликована: Окт. 25, 2024
Язык: Английский
Advanced Science, Год журнала: 2024, Номер unknown
Опубликована: Июль 3, 2024
Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting outcomes, to also include reducing the risk comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery new markers for various health conditions. Integration wearables with intelligent frameworks represents ground-breaking innovations automation operations, conducting advanced large-scale data analysis, generating predictive models, facilitating remote guided clinical decision-making. These substantially alleviate socioeconomic burdens, creating a paradigm shift diagnostics, revolutionizing medical assessments technology development. This review explores critical topics recent progress development 1) systems solutions physiological monitoring, as well 2) discussing current trends adoption smart technologies within settings developing biological assays, ultimately 3) exploring utilities platforms discovery. Additionally, translation from research labs broader applications. It addresses associated risks, biases, challenges widespread Artificial Intelligence (AI) integration diagnostics systems, while systematically outlining potential prospects, challenges, opportunities.
Язык: Английский
Процитировано
17
Rheumatology Science and Practice, Год журнала: 2023, Номер 61(4), С. 397 - 420
Опубликована: Авг. 31, 2023
Two fundamental pathologic processes are central to the spectrum of chronic inflammation mechanisms: autoimmunity and autoinflammation. Autoimmunity autoinflammation mutually potent processes; their development is considered within framework “immunoinflammatory” continuum, reflecting close relationship between innate acquired types immune response. leading mechanism pathogenesis a large group inflammatory human diseases, defined as autoimmune frequency which in population exceeds 10%. Advances molecular biology, pharmacogenetics bioinformatics have created prerequisites for individualization therapy rheumatic diseases concept personalized medicine. The study immunopathogenesis mechanisms, improvement diagnostics, deciphering nature taxonomy, approaches prevention among priority directions medicine 21st century.
Язык: Английский
Процитировано
16
European Journal of Medicinal Chemistry, Год журнала: 2024, Номер 276, С. 116706 - 116706
Опубликована: Июль 22, 2024
Язык: Английский
Процитировано
6
iScience, Год журнала: 2025, Номер 28(2), С. 111754 - 111754
Опубликована: Янв. 6, 2025
Lupus erythematosus is a heterogeneous autoimmune disease that requires treatments tailored to specific patient subsets. To evaluate in silico the efficacy of anti-IFNα S95021 monoclonal antibody, we created quantitative systems pharmacology model cutaneous lupus and virtual population, with attributes matching diversity actual patients. this aim, performed multiomics profiling analysis 337 patients from PRECISESADS cohort, thereby identifying four clusters distinct immune dysregulation patterns, including various levels type I interferon (IFN) pathway upregulation. Simulation treatment cohort (n = 241) predicted clinical responses clusters, machine learning further revealing biomarkers distinguish responders non-responders. Combining mechanistic mathematical modeling supports precision medicine by predicting drug based upon characteristics complex disease.
Язык: Английский
Процитировано
0
Frontiers in Medicine, Год журнала: 2025, Номер 12
Опубликована: Апрель 9, 2025
Introduction The fields of allergy and immunology are increasingly recognizing the transformative potential artificial intelligence (AI). Its adoption is reshaping research directions, clinical practices, healthcare systems. However, a systematic overview identifying current statuses, emerging trends, future hotspots lacking. Methods This study applied bibliometric analysis methods to systematically evaluate global landscape AI applications in immunology. Data from 3,883 articles published by 21,552 authors across 1,247 journals were collected analyzed identify leading contributors, prevalent themes, collaboration patterns. Results Analysis revealed that USA China currently output scientific impact this domain. methodologies, especially machine learning (ML) deep (DL), predominantly drug discovery development, disease classification prediction, immune response modeling, decision support, diagnostics, system digitalization, medical education. Emerging trends indicate significant movement toward personalized systems integration. Discussion findings demonstrate dynamic evolution immunology, highlighting broadening scope basic diagnostics comprehensive Despite advancements, critical challenges persist, including technological limitations, ethical concerns, regulatory frameworks could potentially hinder further implementation Conclusion holds considerable promise for advancing globally enhancing precision, efficiency, accessibility. Addressing existing technological, ethical, will be crucial fully realizing its potential, ultimately improving health outcomes patient well-being.
Язык: Английский
Процитировано
0
Cells, Год журнала: 2025, Номер 14(1), С. 36 - 36
Опубликована: Янв. 2, 2025
Chronic inflammation is increasingly recognized as a critical factor in female reproductive health; influencing natural conception and the outcomes of assisted technologies such vitro fertilization (IVF). An essential component innate immunity, NLR family pyrin domain-containing 3 (NLRP3) inflammasome one major mediators inflammatory responses, its activation closely linked to oxidative stress. This interaction contributes decline oocyte quality, reduced potential, impaired embryo development. In ovarian milieu, stress NLRP3 interact intricately, their combined effects on competence are significant. The aims this review examine these molecular mechanisms explore therapeutic strategies targeting activity, with goal enhancing fertility improving clinical health.
Язык: Английский
Процитировано
0
Journal of Pharmaceutical and Biological Sciences, Год журнала: 2025, Номер 12(2), С. 109 - 118
Опубликована: Янв. 9, 2025
Because of their diverse clinical manifestations and intricate pathophysiology, autoimmune diseases which are defined by the immune system wrongly attacking healthy tissues present serious difficulties. Artificial intelligence (AI) has shown revolutionary promise in this field, especially improving diagnostic precision, facilitating tailored treatment plans, offering real-time illness tracking. This paper highlights AI's role assessing various datasets pertaining to function pathology while critically examining applications AI therapy diseases. In order find new biomarkers enable early accurate detection disorders, advanced approaches such as machine learning deep have proven essential. AI-powered predictive models demonstrated predicting periods remission disease flares, allowing for prompt focused modifications. Furthermore, accelerating identification promising therapeutic candidates lowering related costs, is transforming drug discovery repurposing. However, issues including data heterogeneity, algorithmic transparency, patient confidence AI-driven suggestions limit full potential need ethical frameworks interdisciplinary collaboration these limits suggesting solutions. shows transform diagnosis, treatment, management disorders combining recent developments future applications. will pave way a where healthcare solutions proactive, accurate, individualized.
Язык: Английский
Процитировано
0
Steroids, Год журнала: 2025, Номер unknown, С. 109601 - 109601
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
Current Rheumatology Reports, Год журнала: 2023, Номер 26(3), С. 81 - 88
Опубликована: Дек. 29, 2023
Язык: Английский
Процитировано
8
médecine/sciences, Год журнала: 2024, Номер 40(4), С. 369 - 376
Опубликована: Апрель 1, 2024
L’intelligence artificielle (IA) et l’apprentissage automatique produisent des modèles prédictifs qui aident à la prise de décisions dans le processus découverte nouveaux médicaments. Cette modélisation par ordinateur permet représenter l’hétérogénéité d’une maladie, d’identifier cibles thérapeutiques, concevoir optimiser candidats-médicaments d’évaluer ces médicaments sur patients virtuels, ou jumeaux numériques. En facilitant fois une connaissance détaillée caractéristiques en prédisant les propriétés multiples possibles, l’IA l’émergence médecine précision « computationnelle » offrant traitements parfaitement adaptés aux spécificités patients.
Процитировано
2