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26 articles for “sensitive personal data”
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Architectural and Technological Progress in Modern Mobile Computing
Abstract: Over the last decade, mobile technologies have experienced rapid and transformative growth, reshaping the way individuals interact with the world and redefining multiple sectors, including healthcare, education, communication, and commerce. Continuous improvements in mobile hardware, such as faster processors, enhanced sensors, and longer-lasting batteries, have significantly improved device performance and usability. At the same time, the widespread development of mobile applications has expanded the functional scope of smartphones, enabling personalized, …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 20–31 Read article
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Pharmacogenomics in Anesthesia: Case Studies and Clinical Applications for Personalized Care
Abstract: Pharmacogenomics, the study of how genetic variability influences individual responses to medications, is transforming anesthetic practice by enabling personalized care. This case study collection explores the integration of pharmacogenomic insights into anesthesia management, highlighting its impact on safety, efficacy, and patient outcomes. Adverse reactions to anesthetics often arise from genetic polymorphisms that alter drug metabolism or sensitivity. For instance, patients with RYR1 mutations are susceptible to malignant hyperthermia (MH) when …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 85–91 Read article
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Mental Health in the Post-Pandemic Era (COVID-19): Community-Based Interventions for Resilience and Well-Being
Abstract: Background: The COVID-19 pandemic has had a major psychological effect, causing anxiety, depression, stress, and social disruption around the world. Community-level mental health programs have become widely available methods for promoting resilience and mental well-being, especially in resource-limited contexts. Aim: The aim was to assess the effectiveness of community-based mental health interventions in promoting psychological resilience and overall well-being in the post-pandemic period. Methodology: A cross-sectional, mixed-method, community-based study was …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article