Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

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Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis by Marcos Uceta, Alberto del Cerro‐León, Danylyna Shpakivska‐Bilán, Luis M. García‐Moreno, Fernando Maestú, Luis Fernando Antón‐Toro

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Many-Objective Truss Structural Optimization Considering Dynamic and Stability Behaviors by João Marcos P. Vieira, José Pedro G. Carvalho, Dênis E. C. Vargas, Érica C. R. Carvalho, Patrícia H. Hallak, Afonso C. C. Lemonge

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Clinical diagnosis of partial or complete anterior cruciate ligament tears using patients' history elements and physical examination tests. by Simon Décary, Michel Fallaha, Sylvain Belzile, Johanne Martel-Pelletier, Jean-Pierre Pelletier, Debbie Feldman, Marie-Pierre Sylvestre, Pascal-André Vendittoli, François Desmeules

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Medicare part D prescribing for direct oral anticoagulants in the United States: Cost, use and the "rubber effect". by Panayiotis D Ziakas, Irene S Kourbeti, Loukia S Poulou, Georgios S Vlachogeorgos, Eleftherios Mylonakis

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Comparative Assessment of the Dynamics of Visual Performance of a Patient with Visually Intense Work with Binocular Cataract after Various Technologies of Cataract Phacoemulsificat... by D. F. Pokrovsky, I. B. Medvedev, N. I. Ovechkin, I. G. Ovechkin, A. I. Pavlov

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Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging by James William Ampofo, Christian Ven Emery, Ishmael Nii Ofori

“…Medical imaging has benefited from AI by reducing radiation risks through algorithms used in examinations, referral protocols, and scan justification. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…The novelty of this research lies in the inclusion of 16 event categories to broaden coverage and the implementation of the SMFCNN and transformer-based algorithms. This study highlights the potential of deep learning and transformer-based models in enhancing the accuracy and generalizability of multiclass classification in low-resource languages Urdu.…”
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Network pharmacology and AI in cancer research uncovering biomarkers and therapeutic targets for RALGDS mutations by S. Mohammed Zaidh, Hariharan Thirumalai Vengateswaran, Mohammad Habeeb, Kiran Balasaheb Aher, Girija Balasaheb Bhavar, N. Irfan, K N V Chenchu Lakshmi

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Dataset of apples for grading by sweetness, ripeness and varietyMendeley Data by Shilpa Gaikwad, Sonali Kothari, Ignisha Rajathi G

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Voices of People With Disabilities: Integrating Topic Modeling and Sentiment Analysis to Study Disability Discourse on Social Media by Richard K. Lomotey, Sandra Kumi, Christian Nyaku, Ralph Deters

“…The themes discovered across at least two subreddits are Mobility, Diagnosis, Education, Assistive and Accessible Technology, Support, Disability Accommodations, and Relations. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…One possible result of AI integration is the early detection of diseases, especially in rural locations where access to expert medical care is limited. Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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Systemic longitudinal immune profiling identifies proliferating Treg cells as predictors of immunotherapy benefit: biomarker analysis from the phase 3 CONTINUUM and DIPPER trials by Sai-Wei Huang, Wei Jiang, Sha Xu, Yuan Zhang, Juan Du, Ya-Qin Wang, Kun-Yu Yang, Ning Zhang, Fang Liu, Guo-Rong Zou, Feng Jin, Hai-Jun Wu, Yang-Ying Zhou, Xiao-Dong Zhu, Nian-Yong Chen, Cheng Xu, Han Qiao, Na Liu, Ying Sun, Jun Ma, Ye-Lin Liang, Xu Liu

“…Further validation through flow cytometry (n = 120) confirmed the predictive value of this Treg subset. Multiplex immunohistochemistry (n = 249) demonstrated that Ki67+ Tregs in tumors could predict immunotherapy benefit, with aPD1 improving EFS only in patients with low baseline levels of Ki67+ Tregs. …”
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GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science by Peder V. Nelson, Russanne Low, Holli Kohl, David Overoye, Di Yang, Xiao Huang, Sriram Chellappan, Farhat Binte Azam, Ryan M. Carney, Monika Falk, Joan Garriga, Larisa Schelkin, Rebecca Boger, Theresa Schwerin

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All‐in‐one perovskite memristor with tunable photoresponsivity by Guan‐Hua Dun, Yuan‐Yuan Li, Hai‐Nan Zhang, Fan Wu, Xi‐Chao Tan, Ken Qin, Yi‐Chu He, Ze‐Shu Wang, Yu‐Hao Wang, Tian Lu, Shi‐Wei Tian, Dan Xie, Jia‐Li Peng, Xiang‐Shun Geng, Xiao‐Tong Zhao, Jia‐He Zhang, Yu‐Han Zhao, Xiaoyu Wu, Ning‐Qin Deng, Zheng‐Qiang Zhu, Yan Li, Xian‐Zhu Liu, Xing Wu, Weida Hu, Peng Zhou, Yang Chai, Mario Lanza, He Tian, Yi Yang, Tian‐Ling Ren

“…As a result, the memristor showed a large tunable ratio of 35.9 dB, while its photoresponsivity presented a maximum of 2.7 × 103 mA W−1 and a long‐term memory behavior with over 104 s, making it suitable for realizing all‐in‐one processing tasks. By mapping the algorithm parameters onto the photoresponsivity, we successfully performed both recognition and processing tasks based on the TPR memristor array. …”
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Remote Sensing in the 15 µm CO₂ Band: Key Concepts and Implications for the Heat Balance of Mesosphere and Thermosphere by Alexander Kutepov, Artem Feofilov, Ladislav Rezac, Konstantinos S. Kalogerakis

“…We investigated the algorithms and physical models currently applied to remote sensing of the mesosphere and lower thermosphere (MLT) using space-based observations of the CO₂ 15 µm emission. …”
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Design, Construction, and Evaluation of an Automatic Feeder Control System for Sugarcane Billet Planters by B. Abbasian, M. E. Khorasani Ferdavani, H. Zaki Dizaji

“…It delivered performance that matches manual control in terms of cane spillage reduction and planting quality, all while eliminating the need for an operator. …”
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Artificial Intelligence in Healthcare: Medical Students' Perspectives on Balancing Innovation, Ethics, and Patient-Centered Care by Eleanor Roy, Sara Malafa, Lina M. Adwer, Houda Tabache, Tanishqa Sheth, Vasudha Mishra, Moaz Elsayed Abouelmagd, Andrea Cushieri, Sajjad Ahmed Khan, Mihnea-Alexandru Gaman, Juan C. Puyana, Francisco Javier Bonilla-Escobar

“…However, this transformation also introduces pressing ethical challenges, particularly concerning autonomy, algorithmic bias, and data privacy. In this editorial, we explore these issues through the lens of medical students and future physicians, emphasizing the need for ethical vigilance and proactive governance in the deployment of AI technologies in clinical settings. …”
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Immune Microenvironment Characterization and Machine Learning-Guided Identification of Diagnostic Biomarkers for Ulcerative Colitis by Zheng Q, Wang L, Zhang Y, Peng J, Hou J, Wang H, Ma Y, Tang P, Li Y, Li H, Chen Y, Li J, Chen Y

“…It employs machine learning algorithms to construct diagnostic models, including an optimal 8-gene model (GATA2, IL8, LAT, NOLC1, SMARCA5, SMC3, STX10, ZMIZ1), which demonstrates high predictive performance (AUC of 0.964 in training datasets and 0.884 in testing datasets). …”
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Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles by Anxun Zhang, Longjie Wang, Xiaowei Zhai, Yao Xiao, Yanchan Wu, Yongxi Zhao, Kai Liu, Ji‐Shen Zheng, Dong Chen

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