63477 research outputs found
Sort by
Advancing explainable AI in healthcare: Necessity, progress, and future directions
No full textClinicians typically aim to understand the shape of the liver during treatment planning that could potentially minimize any harm to the surrounding healthy tissues and hepatic vessels, thus, constructing a precise geometric model of the liver becomes crucial. Over the years, various methods for liver image segmentation have emerged, with machine learning and computer vision techniques gaining rapid popularity due to their automation, suitability, and impressive results. Artificial Intelligence (AI) leverages systems and machines to emulate human intelligence, addressing real-world problems. Recent advancements in AI have resulted in widespread industrial adoption, showcasing machine learning systems with superhuman performance in numerous tasks. However, the inherent ambiguity in these systems has hindered their adoption in sensitive yet critical domains like healthcare, where their potential value is immense. This study focuses on the interpretability aspect of machine learning methods, presenting a literature review and taxonomy as a reference for both theorists and practitioners. The paper systematically reviews explainable AI (XAI) approaches from 2019 to 2023. The provided taxonomy aims to serve as a comprehensive overview of XAI method traits and aspects, catering to beginners, researchers, and practitioners. It is found that explainable modeling could potentially contribute to trustworthy AI subject to thorough validation, appropriate data quality, cross validation, and proper regulation.This work was supported by the Medical Research Center, Hamad Medical Corporation Doha, Qatar, under Grant MRC-01-19-327. Open access funding was provided by Qatar National Library
Pharmacological interventions targeting β-adrenoceptors in colorectal cancer: an evolving paradigm
No full textColorectal cancer (CRC) is a significant global health challenge, ranking as the third most common cancer and the second leading cause of cancer-related deaths worldwide. Its development is influenced by several risk factors, including smoking, diets rich in red meat, and the effects of stress-related hormones such as epinephrine and norepinephrine. These hormones act through β-adrenergic receptors (β-ARs), which are present on CRC cells and are associated with cancer-promoting processes such as increased cell growth, invasion, blood vessel formation, and accelerated disease progression. Notably, β-ARs blockers have shown potential in slowing CRC progression, pointing to a promising therapeutic strategy. This review explores the main signaling pathways through which β-ARs contribute to cancer development and how various risk factors may influence these mechanisms. We also provide an overview of current preclinical and clinical studies on β-AR blockers in CRC, identify existing gaps in knowledge, and propose directions for future research to optimize therapeutic outcomes.Open Access funding provided by the Qatar National Library. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript
The effectiveness of a Professional Development Program based on Global Professional Standards for enhancing the elementary teachers' Educational Competencies in Jordan
No full textهدفت الدراسة الحالية إلى استقصاء فاعلية برنامج تدريبي مستند إلى المعايير المهنية للمعلمين في تعزيز الكفايات التعليمية لدى عينة من معلمي التعليم الأساسي في الأردن. تكوَّن أفراد الدراسة من (83) مشاركًا، اختيروا بالطريقة القصدية، وتكونت المجموعة التجريبية من (40) معلمًا ومعلمة، والمجموعة الضابطة من (43) معلمًا ومعلمة. ولتحقيق أهداف الدراسة، طُوِّر برنامج التطوير المهني المستند إلى المعايير المهنية العالمية للمعلمين الذي تكوَّن من أبعاد ثمانية، وتُحُقِّق من صدقه من خلال المحكمين. ولاختبار فرضيتَي الدراسة، طُوِّر مقياس الكفايات التعليمية وجرى التحقق من خصائصه السيكومترية. أظهرت نتائج تحليل التباين المتعدد الأحادي المصاحب (ANOVA) وجود فروق دالة إحصائيًا بين المتوسطات الحسابية لدرجات المعلمين والمعلمات على مقياس الأداء التعليمي حسب المجموعة، وذلك لصالح أفراد المجموعة التجريبية. كذلك أظهرت نتائج اختبار تحليل التباين الثنائي المتعدد (MANOVA) وجود فروق دالة إحصائيًا تُعزى إلى متغير التخصص عند جميع الأبعاد، باستثناء بعد (الإعداد والتخطيط)، وذلك لصالح التخصصات العلمية، وعدم وجود فروق دالة إحصائيًا تُعزى إلى متغير الخبرة عند جميع الأبعاد، وعدم وجود فروق دالة إحصائيًا تُعزى إلى التفاعل بين متغيرَي التخصص والخبرة.The main purpose of the current study is to investigate the effectiveness of a training program based on professional standards for teachers in enhancing the educational competencies of a sample of basic education teachers in Jordan. The study members consisted of (83) participants, selected by the Purposive sampling method. The experimental group consisted of (40) male and female teachers, while the control group comprised (43) male and female teachers. To achieve the objectives of the study, a professional development program based on international professional standards for teachers was developed. It consisted of eight dimensions and its validity was verified by expert reviewers. To test the two hypotheses of the study, an educational competencies scale was developed and its psychometric properties were verified. The ANOVA results showed statistically significant differences between the arithmetic mean scores of male and female teachers on the educational competencies scale, in favor of the experimental group. Meanwhile, the MANOVA results showed statistically significant differences attributed to the specialization variable in all dimensions, except for (preparation and planning dimension), in favor of science specializations. They also showed no statistically significant differences attributed to the experience variable in all dimensions, and no statistically significant differences attributed to the interaction between the variables of specialization and experience
Deep learning in automated power line inspection: A review
No full textIn recent years, power line maintenance has seen a paradigm shift by moving towards computer vision-powered automated inspection. The utilization of an extensive collection of videos and images has become essential for maintaining the reliability, safety, and sustainability of electricity transmission. A significant focus on applying deep learning techniques for enhancing power line inspection processes has been observed in recent research. A comprehensive review of existing studies has been conducted in this paper, to aid researchers and industries in developing improved deep learning-based systems for analyzing power line data. The conventional steps of data analysis in power line inspections have been examined, and the body of current research has been systematically categorized into two main areas: the detection of components and the diagnosis of faults. A detailed summary of the diverse methods and techniques employed in these areas has been encapsulated, providing insights into their functionality and use cases. Special attention has been given to the exploration of deep learning-based methodologies for the analysis of power line inspection data, with an exposition of their fundamental principles and practical applications. Moreover, a vision for future research directions has been outlined, highlighting the need for advancements such as edge–cloud collaboration, and multi-modal analysis among others. Thus, this paper serves as a comprehensive resource for researchers delving into deep learning for power line analysis, illuminating the extent of current knowledge and the potential areas for future investigation
Aggressive management and liver transplantation in Budd-Chiari syndrome secondary to Behçet's disease
No full textBudd-Chiari Syndrome (BCS) is a rare vascular disorder caused by hepatic venous outflow obstruction, often due to thrombosis, leading to liver congestion and portal hypertension. Behçet's Disease (BD), a chronic vasculitis, can cause BCS through inflammation-induced thrombosis. We report a 14-year-old male with BD who developed BCS. He initially presented with foot pain, uveitis, and a bilateral rash, later progressing to abdominal distension, jaundice, and hepatic dysfunction. Investigations revealed elevated transaminases and hyperbilirubinemia, with imaging confirming hepatic vein thrombosis. Management included corticosteroids, immunosuppressants, and anticoagulation. Despite treatment, liver function deteriorated, necessitating a transplant, after which he stabilized with significant symptomatic improvement. This case underscores the need for early recognition of BD-related vascular complications, timely intervention to prevent irreversible liver damage, and consideration of liver transplantation in severe BCS. Increased awareness of BD as a potential cause of BCS is crucial for prompt diagnosis and management
Islamic reasoning and the use of prohibited medicines among Muslim patients: a qualitative study
No full textIntroduction: Muslim patients may avoid medicines containing ingredients prohibited by their faith (haram), such as alcohol, gelatine, or porcine derivatives. While Islamic law permits exceptions based on necessity (darura) or biotransformation (istihala), the way these principles influence medication adherence and shape patient-healthcare provider (HCP) interaction is underexplored. Aim: To explore how Muslims apply Islamic reasoning to medication adherence decisions involving medicines containing haram ingredients. Method: Thirteen ethnically diverse Muslim adults were purposively sampled for semi-structured interviews. A prior scoping review and mosque-based public and patient involvement (PPI) informed the interview guide. Interview data were analysed using Braun and Clarke's Reflexive Thematic Analysis (RTA), with themes constructed inductively. Data interpretation was guided by the Necessity-Concerns Framework (NCF) and locus of control (LOC) theory. Rigour was supported through member checking, peer debriefing and reflexive journalling. Results: Four themes emerged: (1) Halal as worldview: the halal-haram spectrum functioned as a moral lens for daily behaviour and intake, extending to medication use. (2) Motivations for consumption: halal was linked to perceived health and spiritual benefit, while haram signalled impurity and harm. (3) Minor illness or major disease: darura and istihala were applied flexibly in chronic or life-threatening illness, whereas participants avoided prohibited medicines for minor conditions, favouring complementary remedies. Practical workarounds included switching dosage forms or opening gelatine capsules and discarding the shell to minimise religious harm. Decisions were shaped by perceived severity, symptom burden, financial considerations, and the extent to which HCPs were perceived as trustworthy, culturally competent, and responsive to religious disclosure, all of which influenced adherence. (4) Personalised care: participants valued shared decision-making, transparent disclosure of religiously relevant excipients, and a reasonable degree of religious literacy among HCPs; scepticism about halal certification underscored the need for clearer labelling and guidance. Conclusion: Islamic reasoning influenced how participants engaged with medicines deemed haram. Supporting adherence requires pharmacy practice that incorporates religious literacy and responds to concerns about transparent labelling and faith-sensitive communication. These steps will strengthen patient-centred care by aligning religious and ethical reasoning with treatment decisions, fostering trust, enhancing adherence, and supporting more equitable care for Muslim patients.This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Open access funding was provided by Qatar University.Scopu
Author Correction: Global burden of chikungunya virus infections and the potential benefit of vaccination campaigns (Nature Medicine, (2025), 31, 7, (2342-2349), 10.1038/s41591-025-03703-w)
No full textCorrection to: Nature Medicinehttps://doi.org/10.1038/s41591-025-03703-w, published online 10 June 2025. In the version of the article initially published, our code regarding the calculation of Years of Life lived with a Disability (YLDs) was incorrect, affecting our estimated numbers of Disability Adjusted Life Years (DALYs). None of the other estimates (infections, cases, deaths, doses used) were affected. The net effect is to increase the annual DALY burden from chikungunya from 121,000 to 284,000 and the number of DALYs averted per 100,000 vaccine doses used from 17 to 37. The corrections affect the DALYs estimates in the main text, in Fig. 3b and in Supplementary Tables 3 and 4 as well as estimates of averted DALYs presented in the main text, in Figs. 4, 5 and in Extended Data Fig. 3a. The HTML and PDF versions of the article have been corrected and the original, uncorrected Figs. 3–5 and Extended Data Fig. 3 are included as Supplementary information alongside this notice for comparison
The impact of congruence on consumer engagement with brands on social media
No full textThis study examines the mechanisms behind the effectiveness of influencer marketing on social media and its role in shaping consumer engagement. Therefore, the study surveyed 703 Tunisian consumers on Instagram, analyzing different forms of congruence (brand-influencer, brand-consumer, and influencer-consumer) and their impact on consumer engagement with brands on social media. The study's findings reveal that consumer engagement significantly influences brand image and visit intention. However, while influencer-consumer congruence and brand-influencer congruence strongly affect engagement indicators, brand-consumer congruence does not show a significant effect on consumer engagement. Consumer engagement acts as a key mediator, positively influencing brand image and visit intention. These results offer valuable insights for marketing professionals seeking to optimize their social media influence strategies, particularly regarding influencer selection and the importance of fostering authentic connections with target audiences.This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Project No. KFU252038].Scopu
Hormonal Modulation of Fat Mass Induced Insulin Resistance
No full textObjective: This study examines the impact of body mass index (BMI) on homeostatic model assessment for insulin sensitivity (HOMA-S) and homeostatic model assessment for pancreatic β-cell function (HOMA-B) in adults with obesity but without diabetes. Additionally, the association of key hormones, leptin and gastric inhibitory peptide (GIP), with HOMA indices and BMI has been investigated. Methods: This cross-sectional study involved 289 adults without diabetes from Hamad General Hospital in Qatar. BMI was analyzed as a predictor of HOMA-S and HOMA-B using adjusted multivariable linear regression. A logistic regression model was used to investigate hormonal predictors of insulin sensitive phenotype (ISP), and results were presented using margins plots, stratified by obesity classes. Results: We found a strong, linear dose-response relationship between BMI and HOMA indices, with each unit increase in BMI linked to approximately a 2% decline in HOMA-S and a 1% rise in HOMA-B. Subgroup analysis revealed that the effects on ISP were more strongly driven by hormonal variations, particularly leptin and GIP levels, than by BMI alone. Conclusions: Our findings demonstrate that BMI is a proxy for hormonal variations, particularly in leptin and GIP, which more strongly predict insulin sensitivity. These results support the need for incorporating hormonal markers into obesity-related risk assessment and management strategies.The Study was funded by Hamad Medical Corporation (MRC#16245/16)
Erratum: The intersection of finTech adoption, HR competency potential, service innovation, and firm growth in the banking sectors using Entropy and TOPSIS (PLoS ONE (2025) 20:1 (e0313210) DOI: 10.1371/journal.pone.0313210)
No full textThe funding statement for this paper is incorrect. The correct funding statement is as follows: This work was supported by the Technology Innovation Program (RS-2024-00487049, Development and demonstration of complex emotion recognition on-device AI technology for in-vehicle driver emotional services), funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).Scopu