The Future of Giant Cell Arteritis Diagnosis and Management: A Systematic Review of Artificial Intelligence and Predictive Analytics DOI Open Access

Mohammed Khaleel I Kh Almadhoun,

Mansi Yadav,

Sayed Dawood Shah

и другие.

Cureus, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

Giant cell arteritis (GCA), a systemic vasculitis affecting large and medium-sized arteries, poses significant diagnostic management challenges, particularly in preventing irreversible complications like vision loss. Recent advancements artificial intelligence (AI) technologies, including machine learning (ML) deep (DL), offer promising solutions to enhance accuracy optimize treatment strategies for GCA. This systematic review, conducted according the PRISMA 2020 guidelines, synthesizes existing literature on AI applications GCA care, with focus accuracy, outcomes, predictive modeling. A comprehensive search of databases (MEDLINE (via PubMed), Scopus, Cochrane Central Register Controlled Trials (CENTRAL), Web Science) from their inception September 2024 identified 309 studies, four meeting inclusion criteria. The review highlights potential improve through image analysis color Doppler ultrasound clinical data, models random forests, convolutional neural networks, logistic regression demonstrating effectiveness predicting diagnosis relapse after glucocorticoid tapering. Despite these findings, challenges such as need larger datasets, prospective validation, addressing ethical concerns remain. underscores transformative care while emphasizing further research refine validate AI-driven tools broader implementation.

Язык: Английский

A Scientometrics Analytics on Immune system-related conditions and AI-driven computational methods: Trend and Exploration DOI Open Access

Deepti Rani Pattanaik

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, Год журнала: 2025, Номер 09(01), С. 1 - 9

Опубликована: Янв. 17, 2025

In the previous decade, there has been a concerning rise in both prevalence and incidence rates of autoimmune diseases. According to recent studies, these illnesses affect about 10% population, with significantly higher frequency women than men. A comprehensive study conducted UK underscored this trend, revealing significant socioeconomic, seasonal, geographical variations manifestation Furthermore, evidence indicates that individuals diagnosed one condition are at an elevated risk developing additional disorders, although correlation is not uniform across all conditions. The principal purpose research highlight carefully review corpus existing material explores use ML technique framework This includes assessment present level understanding as well embracing impartial advancements, areas requiring improvement, concerns, potential future directions. Utilizing R programming bibliometrix codes, descriptive bibliometric analysis was conducted, resulting matrix encompasses relevant documents. Data sourced from WOS database, During time frame 2002 2025, specifically concentrating on terms "Immune system-related conditions" "AI-driven computational methods." final dataset comprised 419 publications, connection between diseases machine learning. Key themes identified include "Rheumatoid Arthritis," "Pathogenesis," "Inflammation." current landscape, topics such systems, consensus, cell death have gained adhesion. paper provides overview measure linking learning, thereby contributing advancement scientific domain. Keywords:-Immune conditions, AI-driven methods, Scientometric analysis.

Язык: Английский

Процитировано

0
Review of 2024 publications on the applications of artificial intelligence in rheumatology DOI
Mazen Al Zo’ubi

Clinical Rheumatology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 27, 2025

Язык: Английский

Процитировано

0
Cardiotoxicity induced by chemotherapy and immunotherapy in cancer treatment: a bibliometric analysis DOI Creative Commons
Xi Zhang, Yanfeng Xue,

Mingyan Hao

и другие.

Discover Oncology, Год журнала: 2025, Номер 16(1)

Опубликована: Март 23, 2025

New chemotherapy and immunotherapy agents have revolutionized cancer treatment, significantly improving patient survival rates quality of life while extending lifespans. However, these therapies often come with severe side effects, particularly cardiotoxicity. Over the past few decades, this field has seen steady growth. To better understand current trends, research hotspots, collaborative networks in area, a bibliometric analysis relevant literature was conducted. A comprehensive search performed Web Science for articles on cardiotoxicity induced by published SSCI SCI-EXPANDED up to October 21, 2024. Using software tools such as GraphPad Prism, CiteSpace, VOSviewer, we analyzed various parameters including publication year, countries, institutions, journals, authors, references. Additionally, co-occurrence analyses, cooperation relationship assessments, co-citation networks, keyword maps, clustering emergence evaluations were As 2024, total 5290 from 5674 institutions 27,528 authors across 114 countries regions collected. The annual frequency rate steadily increased. United States emerge leading country terms volume, University Texas System being most prolific frequently cited institution. "Breast Cancer Research Treatment" among journals revelant publications. Notable contributors included Ky bonnie Thavendiranathan Paaladinesh, Cardinale D achieved highest average citation count per publication. Current hotspots echocardiography, trastuzumab, doxorubicin, radiotherapy, myocarditis, 5-fluorouracil. trend suggests that is expected play an increasingly critical role treatment. This study provides visualization It highlights developments, efforts, within field, offering essential scientific reference value Cardio-Oncology.

Язык: Английский

Процитировано

0
Trends in nanomedicine for colorectal cancer treatment: Bibliometric and visualization analysis (2010-2024) DOI
Yu-Ren Zhang,

Huirong Zhu,

Haoran Li

и другие.

World Journal of Gastrointestinal Oncology, Год журнала: 2025, Номер 17(4)

Опубликована: Март 24, 2025

Recently, numerous studies have reported the application of nanomedicines in colorectal cancer treatment. However, no systematic bibliometric analysis has been conducted to examine potential and mechanisms action nanomedicine this context. Such an may provide a comprehensive overview current research landscape, identify emerging trends, highlight key areas for future investigation. To describe global landscape on The Web Science Core Collection database was searched literature published from January 1, 2010, August 7, 2024, focusing Bibliometric visualization mapping countries, institutions, authors, keywords, references relevant were using CiteSpace (6.2R6), VOSviewer (1.6.20), bibliometrix (based R 4.3.2). A total 3598 articles included, with rapid increase publication volume starting 2010. China most papers topic, followed by United States India. emerged as central country field, Egyptian Knowledge Bank Chinese Academy Sciences institutions highest number publications. exhibited centrality. prolific author Zhang Y, whereas Siegel RL cited author, Li Y had H-index. International Journal Nanomedicine publications Biomaterials received citations. Keyword co-occurrence identified 11837 keywords grouped into 13 clusters 15 high-frequency highlighted keywords. top three keyword "0 cancer", "1 drug delivery", "2 being "nanoparticles", "colorectal "drug delivery". Research surged since "nanoparticles" Future should investigate nanomaterial stability target-specific release.

Язык: Английский

Процитировано

0
Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques DOI Creative Commons
Azmath Mubeen, Uma N. Dulhare

Rheumato, Год журнала: 2024, Номер 4(4), С. 176 - 192

Опубликована: Окт. 24, 2024

Background/Objectives: Accurate detection and classification of nodules in medical images, particularly rheumatoid nodules, are critical due to the varying nature these where their specific type is often unknown before analysis. This study addresses challenges multi-class prediction nodule detection, with a focus on by employing comprehensive approach feature extraction classification. We utilized diverse dataset including sourced from DermNet local rheumatologists. Method: integrates 62 features, combining traditional image characteristics advanced graph-based features derived superpixel graph constructed through Delaunay triangulation. The key steps include preprocessing anisotropic diffusion Retinex enhancement, segmentation using SLIC, extraction. Texture analysis was performed Gray-Level Co-occurrence Matrix (GLCM) metrics, while shape conducted Fourier descriptors. Vascular pattern recognition, crucial for identifying enhanced Frangi filter. A Hybrid CNN–Transformer model employed fusion, selection hyperparameter tuning were optimized Gray Wolf Optimization (GWO) Particle Swarm (PSO). Feature importance assessed SHAP values. Results: proposed methodology achieved an accuracy 85%, precision 0.85, recall 0.89, F1 measure 0.87, demonstrating effectiveness detecting classifying both binary scenarios. Conclusions: presents robust tool imaging, offering significant potential improving diagnostic aiding early identification conditions.

Язык: Английский

Процитировано

0
The Future of Giant Cell Arteritis Diagnosis and Management: A Systematic Review of Artificial Intelligence and Predictive Analytics DOI Open Access

Mohammed Khaleel I Kh Almadhoun,

Mansi Yadav,

Sayed Dawood Shah

и другие.

Cureus, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

Giant cell arteritis (GCA), a systemic vasculitis affecting large and medium-sized arteries, poses significant diagnostic management challenges, particularly in preventing irreversible complications like vision loss. Recent advancements artificial intelligence (AI) technologies, including machine learning (ML) deep (DL), offer promising solutions to enhance accuracy optimize treatment strategies for GCA. This systematic review, conducted according the PRISMA 2020 guidelines, synthesizes existing literature on AI applications GCA care, with focus accuracy, outcomes, predictive modeling. A comprehensive search of databases (MEDLINE (via PubMed), Scopus, Cochrane Central Register Controlled Trials (CENTRAL), Web Science) from their inception September 2024 identified 309 studies, four meeting inclusion criteria. The review highlights potential improve through image analysis color Doppler ultrasound clinical data, models random forests, convolutional neural networks, logistic regression demonstrating effectiveness predicting diagnosis relapse after glucocorticoid tapering. Despite these findings, challenges such as need larger datasets, prospective validation, addressing ethical concerns remain. underscores transformative care while emphasizing further research refine validate AI-driven tools broader implementation.

Язык: Английский

Процитировано

0