323,104 research outputs found
Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Cancer Detection
No full textAim: Breast cancer (BC) is the most common type of cancer in women, accounting for more than 30% of new female cancers each year. Although various treatments are available for BC, most cancer-related deaths are due to incurable metastases. Therefore, the early diagnosis and treatment of BC are crucial before metastasis. Mammography and ultrasonography are primarily used in the clinic for the initial identification and staging of BC; these methods are useful for general screening but have limitations in terms of sensitivity and specificity. Omics-based biomarkers, like metabolomics, can make early diagnosis much more accurate, make tracking the disease’s progression more accurate, and help make personalized treatment plans that are tailored to each tumor’s specific molecular profile. Metabolomics technology is a feasible and comprehensive method for early disease detection and biomarker identification at the molecular level. This research aimed to establish an interpretable predictive artificial intelligence (AI) model using plasma-based metabolomics panel data to identify potential biomarkers that distinguish BC individuals from healthy controls. Methods: A cohort of 138 BC patients and 76 healthy controls were studied. Plasma metabolites were examined using LC-TOFMS and GC-TOFMS techniques. Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), and Random Forest (RF) were evaluated using performance metrics such as Receiver Operating Characteristic-Area Under the Curve (ROC AUC), accuracy, sensitivity, specificity, and F1 score. ROC and Precision-Recall (PR) curves were generated for comparative analysis. The SHapley Additive Descriptions (SHAP) analysis evaluated the optimal prediction model for interpretability. Results: The RF algorithm showed improved accuracy (0.963 ± 0.043) and sensitivity (0.977 ± 0.051); however, LightGBM achieved the highest ROC AUC (0.983 ± 0.028). RF also achieved the best Precision-Recall Area under the Curve (PR AUC) at 0.989. SHAP search found glycerophosphocholine and pentosidine as the most significant discriminatory metabolites. Uracil, glutamine, and butyrylcarnitine were also among the significant metabolites. Conclusions: Metabolomics biomarkers and an explainable AI (XAI)-based prediction model showed significant diagnostic accuracy and sensitivity in the detection of BC. The proposed XAI system using interpretable metabolite data can serve as a clinical decision support tool to improve early diagnosis processes
sj-docx-2-cat-10.1177_10760296241240748 - Supplemental material for Sex Differences and Clinical Outcomes of Patients with Coronavirus Disease 2019 Infection and Cerebral Venous Sinus Thrombosis: A Systematic Review
No full textSupplemental material, sj-docx-2-cat-10.1177_10760296241240748 for Sex Differences and Clinical Outcomes of Patients with Coronavirus Disease 2019 Infection and Cerebral Venous Sinus Thrombosis: A Systematic Review by Saleh A. Algarni, Naif S. ALGhasab, Mohammed S. Alharbi, Anas Albarrak, Ahmad A. Alanezi and Hamdan M. Al Shehri in Clinical and Applied Thrombosis/Hemostasis</p
sj-docx-1-cat-10.1177_10760296241240748 - Supplemental material for Sex Differences and Clinical Outcomes of Patients with Coronavirus Disease 2019 Infection and Cerebral Venous Sinus Thrombosis: A Systematic Review
No full textSupplemental material, sj-docx-1-cat-10.1177_10760296241240748 for Sex Differences and Clinical Outcomes of Patients with Coronavirus Disease 2019 Infection and Cerebral Venous Sinus Thrombosis: A Systematic Review by Saleh A. Algarni, Naif S. ALGhasab, Mohammed S. Alharbi, Anas Albarrak, Ahmad A. Alanezi and Hamdan M. Al Shehri in Clinical and Applied Thrombosis/Hemostasis</p
Diffusive author(s), cohesive author: Analysis of S/N (1994)
No full textThis study indicates the ways in which various aspects of the author(s) are brought forth in Dumb type’s performance art, the S/N production. Previous research has suggested a non-hierarchical organization of Dumb type and the absence of a “privileged author” in Dumb type’s collaborative work, S/N. However, the results that I have investigated from member’s interviews on the creative process of S/N along with my analysis of the recorded images of S/N, indicate a different aspect of the author(s). First, S/N was created through, so to speak, the collective ideas of the members of Dumb type. Further, S/N has at least nine quotations from previous performances, installations, and printed writings, besides the work-in-progress technique. Explicating one of the “author functions” as given by Michel Foucault, each text has plural subjects of the author. However, it has been revealed from members’ interviews that Teiji Furuhashi had a decision-making role in selecting the members’ ideas within the performance. Since then, S/N has had plural subjects of creation; however, Furuhashi is one of the subjects of creation along with the “privileged author.” S/N has plural authors (diffusive authors) yet at the same time, it has a “privileged author,” Teiji Furuhashi (cohesive author)
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
sj-pdf-1-tui-10.1179173X221075581 – Supplemental Material for Effects of Abstinence Self-Efficacy and Outcome Expectancies of Tobacco Smoking on the Desire to Quit Among Saudi Women: A Cross-Sectional Mediation Analysis
No full textSupplemental Material, sj-pdf-1-tui-10.1179173X221075581 for Effects of Abstinence Self-Efficacy and Outcome Expectancies of Tobacco Smoking on the Desire to Quit Among Saudi Women: A Cross-Sectional Mediation Analysis by Abdullah M Alanazi, Shahad F Almutairi, Alanoud A Alsarami, Fay J Alanazi, Lama H Alqahtani, Tareq F Alotaibi, Saleh S Algarni, Sarah S Monshi and Taha T Ismaeil in tobacco use insights</p
sj-docx-2-smo-10.1177_20503121241247458 – Supplemental material for Epilepsy first aid awareness among healthcare workers in Saudi Arabia: A cross-sectional study
No full textSupplemental material, sj-docx-2-smo-10.1177_20503121241247458 for Epilepsy first aid awareness among healthcare workers in Saudi Arabia: A cross-sectional study by Anas M Albarrak, Ali A AlAseeri, Ahmed A Albadrani, Mohammed Saad Alqahtani, Daifallah M Almalki, Saleh A Algarni, Abdullah S Al-Dosary and Ibrahim Abdulrahman I Alquwaiz in SAGE Open Medicine</p
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
sj-docx-1-smo-10.1177_20503121241247458 – Supplemental material for Epilepsy first aid awareness among healthcare workers in Saudi Arabia: A cross-sectional study
No full textSupplemental material, sj-docx-1-smo-10.1177_20503121241247458 for Epilepsy first aid awareness among healthcare workers in Saudi Arabia: A cross-sectional study by Anas M Albarrak, Ali A AlAseeri, Ahmed A Albadrani, Mohammed Saad Alqahtani, Daifallah M Almalki, Saleh A Algarni, Abdullah S Al-Dosary and Ibrahim Abdulrahman I Alquwaiz in SAGE Open Medicine</p
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