Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…Harnessing social media language analytics can strengthen early detection systems, guide geographically targeted public health messaging, and inform policy efforts aimed at reducing opioid-related harm and improving pain management equity.…”
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Multimodal learning for enhanced SPECT/CT imaging in sports injury diagnosis by Zhengzheng Jiang, YaWen Shen

“…This study further incorporates a biomechanics-aware injury detection module (BID-Net), which leverages kinematic signals, motion data, and physiological context to refine lesion detection accuracy.ResultsExperimental results on a curated sports injury dataset demonstrate that our framework significantly improves image clarity, diagnostic precision, and interpretability over traditional approaches.DiscussionThe integration of biomechanical constraints and adaptive attention mechanisms not only enhances SPECT/CT imaging quality but also bridges the gap between AI-driven analytics and clinical practice in sports medicine. …”
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Microsaccades: Empirical Research and Methodological Advances by Susana Martinez-Conde, Ralf Engbert, Rudolf Groner

“…In “Motion tracking of iris features to detect small eye movements” Chaudhary and Pelz describe a new video-based eye tracking methodology that relies on higher-order iris texture features, rather than on lower-order pupil center and corneal reflection features, to detect microsaccades with high confidence. …”
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Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses by İsmail Baydili, Burak Tasci, Gülay Tasci

“…Speech analysis frameworks, leveraging large language models (LLMs), have improved the detection of cognitive impairments and psychiatric symptoms through nuanced linguistic feature extraction. …”
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Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training by Yi Xiang, Rajendra Acharya, Quan Le, Jen Hong Tan, Chiaw-Ling Chng

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Attention-based hybrid deep learning model with CSFOA optimization and G-TverskyUNet3+ for Arabic sign language recognition by Ahmed A. Mohamed, Abdullah Al-Saleh, Sunil Kumar Sharma, Ghanshyam Tejani

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A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

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The Ion Formation and Quantitative Response of Isoprene, Monoterpenes and Terpenoids in Ion Mobility Spectrometry with Atmospheric-Pressure Chemical Ionization as a Function of Tem... by Thomas Mayer, Ralf Petrich, Helko Borsdorf

“…A drift tube temperature above 120 °C permitted the most sensitive detection of isoprene and monoterpenes, while 80 °C was sufficient for the sensitive detection of most terpenoids. …”
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A New Approach for Carrying Out Sentiment Analysis of Social Media Comments Using Natural Language Processing by Mritunjay Ranjan, Sanjay Tiwari, Arif Md Sattar, Nisha S. Tatkar

“…Pragmatics include personality recognition, sarcasm detection, metaphor comprehension, aspect extraction, and polarity detection; semantics include word sense disambiguation, concept extraction, named entity recognition, anaphora resolution, and subjectivity detection.…”
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Predicting Soccer Player Salaries with Both Traditional and Automated Machine Learning Approaches by Davronbek Malikov, Pilsu Jung, Jaeho Kim

“…Despite the increasing use of performance data in sports analytics, a critical gap remains in establishing fair compensation models that comprehensively account for both quantifiable and intangible contributions. …”
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Multimodal approaches and AI-driven innovations in dementia diagnosis: a systematic review by Revati M. Wahul, Sarita Ambadekar, Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Manisha A. Dudhedia, Varsha Gaikwad, Bhavana Kanawade, J. R. Pansare, Balaji Bodkhe, S. H. Gawande

“…A complete review of peer-reviewed papers over the past ten years, with a focus on Machine Learning, Deep Learning, and multimodal fusion approaches to enhance diagnostic and therapeutic precision will focus on neuroimaging biomarkers, EEG-based cognitive profiles, digital phenotyping, and wearable sensor analytics. This survey will compare the study’s algorithms or frameworks on sensitivity, specificity, interpretability, computational efficiency, and clinical transnationality concerning early detection and monitoring progression. …”
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Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images by Mahmoud Ragab, Iyad Katib, Sanaa A. Sharaf, Hassan A. Alterazi, Alanoud Subahi, Sana G. Alattas, Sami Saeed Binyamin, Jaber Alyami

“…Also, AI is used to track the progress of patients through treatment. AI-based analytics is used to predict potential tumour recurrence and assess treatment response. …”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…The research endeavors to make a scholarly contribution to the field of cardiology by utilizing predictive analytics to pave the way for improved early detection and diagnosis of heart disease. …”
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Activity Analysis of the Economic Entity and Digital Culture by E. B. Gerasimova

“…Detection of the positive features and disadvantages of digitalisation of the economy. …”
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A Comprehensive Analysis of the Security of ML Integrated CPS as Autonomous Vehicles by Kesava reddy, Kumudham R

“…In general, the findings emphasise the significance of leveraging progressive data analytics and ML to improve the security and reliability of autonomous vehicles, confirming the safe functions in progressively multifaceted atmospheres. …”
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FPGA SoC Implementation of Adaptive Deep Neural Network-Based Multimodal Edge Intelligence for Internet of Medical Things by Nikhil B. Gaikwad, Smith K. Khare, Dinesh Mendhe, Hasan Mir, Sokol Kosta, U. Rajendra Acharya

“…The results show that our adaptive DNN model has obtained a software accuracy of 99.2% for ECG, 91.4% for PPG, 95% for activity classification, and 98.7% for smoke detection with a five-fold cross-validation strategy. …”
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COMPARATIVE CHARACTERISTICS OF PIGMENT COMPOSITION FROM RAW MATERIALS AND OIL EXTRACT OF NETTLE LEAVES by O. V. Trineeva, A. I. Slivkin

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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…Machine learning algorithms assist in real-time polyp detection, classification, and predictive analytics, enhancing diagnostic accuracy while reducing inter-observer variability and human error. …”
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The transfer learning of uncertainty quantification for industrial plant fault diagnosis system design by J. Blair, O. Amin, B. D. Brown, S. McArthur, A. Forbes, B. Stephen

“…The performance and confidence in fault detection and diagnostic systems can be undermined by data pipelines that feature multiple compounding sources of uncertainty. …”
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Recent advancements in hybrid electrochemical biosensors nanoarchitectronics by Christopher Igwe Idumah

“…Presently, NMs are versatily utilized in a vast range of electrochemical sensorial uses because of their physically, chemically, as well as biologically inclined features, presenting them as outstanding materials for designing electrode surface for the construction of electrochemical sensors exhibiting outstanding analytical behavior. …”
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