Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers DOI

Hai Xu,

Songsong Ding,

Tong Yu

и другие.

Biological Research For Nursing, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 20, 2024

Background: Obese patients are increasingly recognized as being at higher risk for skin diseases, particularly chronic wounds. While the exact mechanisms remain unclear, obesity is suspected to influence development of injuries via inflammatory biomarkers. Single nucleotide polymorphisms (SNPs) may further gene expression, protein function, and levels biomarkers through various mechanisms, thereby modulating responses that contribute wound pathogenesis. Methods: A two-sample two-step Mendelian Randomization (MR) was employed explore causal relationship between wounds, focusing on mediating role SNPs were used instrumental variables (IVs) infer causality. Obesity-related genetic data sourced from UK Biobank GIANT consortium. Genome-wide association studies provided 92 biomarkers, involving 14,824 575,531 individuals. Pressure injuries, lower limb venous ulcers, diabetic foot ulcer obtained FinnGen R10 Pan-UK Biobank. Results: Obesity significantly increased pressure ulcers. CCL19, hGDNF, IL-12B, TNFRSF9 identified mediators in obesity-induced Conclusion: This study provides evidence leads ulcers suggesting potential therapeutic targets intervention.

Язык: Английский

Exploring the Impact of Artificial Intelligence on Healthcare Management: A Combined Systematic Review and Machine-Learning Approach DOI Creative Commons
Vito Santamato, Caterina Tricase, Nicola Faccilongo

и другие.

Applied Sciences, Год журнала: 2024, Номер 14(22), С. 10144 - 10144

Опубликована: Ноя. 6, 2024

The integration of artificial intelligence (AI) in healthcare management marks a significant advance technological innovation, promising transformative effects on processes, patient care, and the efficacy emergency responses. scientific novelty study lies its integrated approach, combining systematic review predictive algorithms to provide comprehensive understanding AI’s role improving across different contexts. Covering period between 2019 2023, which includes global challenges posed by COVID-19 pandemic, this research investigates operational, strategic, response implications AI adoption sector. It further examines how impact varies temporal geographical addresses two main objectives: explore influences domains, identify variations based Utilizing an we compared various prediction algorithms, including logistic regression, interpreted results through SHAP (SHapley Additive exPlanations) analysis. findings reveal five key thematic areas: enhancing quality assurance, resource management, security, pandemic. highlights positive influence operational efficiency strategic decision making, while also identifying related data privacy, ethical considerations, need for ongoing integration. These insights opportunities targeted interventions optimize current future landscapes. In conclusion, work contributes deeper provides policymakers, professionals, researchers, offering roadmap addressing both

Язык: Английский

Процитировано

7
Machine learning in ocular oncology and oculoplasty: Transforming diagnosis and treatment DOI Open Access

Dipali Vikas Mane,

Khuspe Pankaj Ramdas

IP International Journal of Ocular Oncology and Oculoplasty, Год журнала: 2025, Номер 10(4), С. 196 - 207

Опубликована: Янв. 14, 2025

In the domains of ocular oncology and oculoplasty, machine learning (ML) has become a game-changing technology, providing previously unheard-of levels precision in diagnosis, treatment planning, outcome prediction. Using imaging modalities, genomic data, clinical characteristics, this chapter investigates integration algorithms detection tumours, including retinoblastoma uveal melanoma. Through predictive modelling real-time decision-making, it also emphasises how ML might improve surgical outcomes orbital reconstruction eyelid correction. Automated examination fundus photographs, histological slides, 3D been made possible by methods like deep natural language processing, which have improved individualised therapeutic approaches decreased diagnostic errors. Additionally, use augmented reality robotics surgery is significant development oculoplasty. Notwithstanding its potential, issues data heterogeneity, algorithm interpretability, ethical considerations are roadblocks that need to be addressed. This explores cutting-edge developments, real-world uses, potential future paths, offering researchers doctors thorough resource. Dipali Vikas Mane, Associate Professor, Shriram Shikshan Sanstha’s College Pharmacy, Paniv-413113

Язык: Английский

Процитировано

0
Next-generation agentic AI for transforming healthcare DOI Creative Commons
Nalan Karunanayake

Informatics and Health, Год журнала: 2025, Номер 2(2), С. 73 - 83

Опубликована: Апрель 8, 2025

Язык: Английский

Процитировано

0
Enhancing risk management in hospitals: leveraging artificial intelligence for improved outcomes DOI Creative Commons

Ranieri Guerra

Italian Journal of Medicine, Год журнала: 2024, Номер 18(2)

Опубликована: Апрель 15, 2024

In hospital settings, effective risk management is critical to ensuring patient safety, regulatory compliance, and operational effectiveness. Conventional approaches assessment mitigation frequently rely on manual procedures retroactive analysis, which might not be sufficient recognize respond new risks as they arise. This study examines how artificial intelligence (AI) technologies can improve in healthcare facilities, fortifying safety precautions guidelines while improving the standard of care overall. Hospitals proactively identify mitigate risks, optimize resource allocation, clinical outcomes by utilizing AI-driven predictive analytics, natural language processing, machine learning algorithms. The different applications AI are discussed this paper, along with opportunities, problems, suggestions for their use settings.

Язык: Английский

Процитировано

3
TeleStroke: real-time stroke detection with federated learning and YOLOv8 on edge devices DOI Creative Commons
Abdussalam Elhanashi, Pierpaolo Dini, Sergio Saponara

и другие.

Journal of Real-Time Image Processing, Год журнала: 2024, Номер 21(4)

Опубликована: Июнь 26, 2024

Abstract Stroke, a life-threatening medical condition, necessitates immediate intervention for optimal outcomes. Timely diagnosis and treatment play crucial role in reducing mortality minimizing long-term disabilities associated with strokes. This study presents novel approach to meet these critical needs by proposing real-time stroke detection system based on deep learning (DL) utilization of federated (FL) enhance accuracy privacy preservation. The primary objective this research is develop an efficient accurate model capable discerning between non-stroke cases real-time, facilitating healthcare professionals making well-informed decisions. Traditional methods relying manual interpretation images are time-consuming prone human error. DL techniques have shown promise automating process, yet challenges persist due the need extensive diverse datasets concerns. To address challenges, our methodology involves assessing YOLOv8 models comprehensive comprising both facial paralysis individuals from images. training process empowers grasp intricate patterns features strokes, thereby enhancing its diagnostic accuracy. In addition, learning, decentralized approach, employed bolster while preserving performance. enables learn data distributed across various clients without compromising sensitive patient information. proposed has been implemented NVIDIA platforms, utilizing their advanced GPU capabilities enable processing analysis. optimized potential revolutionize care, promising save lives elevate quality services neurology field.

Язык: Английский

Процитировано

3
Integration of Federated Learning and Blockchain in Healthcare: A Tutorial DOI Creative Commons
Yahya Shahsavari, Oussama Abderrahmane Dambri, Yaser Baseri

и другие.

Опубликована: Апрель 18, 2024

Wearable devices and medical sensors revolutionize health monitoring, raising concerns about data privacy in Machine Learning (ML) for healthcare.This tutorial explores Federated (FL) Blockchain (BC) integration, offering a secure privacy-preserving approach to healthcare analytics.FL enables decentralized model training on local at institutions, keeping patient localized.This facilitates collaborative development without compromising privacy.However, FL introduces vulnerabilities.BC, with its tamper-proof ledger smart contracts, provides robust framework learning FL.After presenting taxonomy the various types of used ML applications, concise review techniques use cases, this three integration architectures balancing decentralization, scalability, reliability data.Furthermore, it investigates how Blockchain-based (BCFL) enhances security collaboration disease prediction, image analysis, drug discovery.By providing FL, blockchain, their along BCFL paper serves as valuable resource researchers practitioners seeking leverage these technologies ML.It aims accelerate advancements analytics, ultimately improving outcomes.

Язык: Английский

Процитировано

1
Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers DOI

Hai Xu,

Songsong Ding,

Tong Yu

и другие.

Biological Research For Nursing, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 20, 2024

Background: Obese patients are increasingly recognized as being at higher risk for skin diseases, particularly chronic wounds. While the exact mechanisms remain unclear, obesity is suspected to influence development of injuries via inflammatory biomarkers. Single nucleotide polymorphisms (SNPs) may further gene expression, protein function, and levels biomarkers through various mechanisms, thereby modulating responses that contribute wound pathogenesis. Methods: A two-sample two-step Mendelian Randomization (MR) was employed explore causal relationship between wounds, focusing on mediating role SNPs were used instrumental variables (IVs) infer causality. Obesity-related genetic data sourced from UK Biobank GIANT consortium. Genome-wide association studies provided 92 biomarkers, involving 14,824 575,531 individuals. Pressure injuries, lower limb venous ulcers, diabetic foot ulcer obtained FinnGen R10 Pan-UK Biobank. Results: Obesity significantly increased pressure ulcers. CCL19, hGDNF, IL-12B, TNFRSF9 identified mediators in obesity-induced Conclusion: This study provides evidence leads ulcers suggesting potential therapeutic targets intervention.

Язык: Английский

Процитировано

0