A Federated Learning-Based Framework for Accurately Identifying Human Activity in the Environment by Nwadher Suliman Al-Blihed, Dina M. Ibrahim

“…Human Activity Recognition (HAR) refers to the detection of people’s activities during daily life using various types of sensors. …”
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Capturing drug use patterns at a glance: An n-ary word sufficient statistic for repeated univariate categorical values. by Gabriel J Odom, Laura Brandt, Clinton Castro, Sean X Luo, Daniel J Feaster, Raymond R Balise, CTN-0094 Team

“…As examples, we provide three algorithms to define primary endpoints from seminal SUD clinical trials.…”
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Identification of atrial fibrillation using heart rate variability: a meta-analysis by Ziwei Yin, Changxin Liu, Chenggong Xie, Zixing Nie, Jiaming Wei, Wen Zhang, Hao Liang

“…Subgroup analyses revealed that both deep learning algorithms (sensitivity = 0.95, specificity = 0.98, AUC = 0.99) and multi-database studies (sensitivity = 0.96, specificity = 0.97, AUC = 0.99) demonstrated enhanced accuracy in AF identification compared to other approaches.ConclusionMachine learning can effectively identify AF with HRV in ECG, especially in diagnosis and detection, with deep learning algorithms and multiple-databases outperforming other diagnostic methods.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, PROSPERO (CRD42025634406).…”
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Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson’s Disease: A Systematic Review and Meta-Analysis by Feng Zhang, Liangqing Guo, Lin Liu, Xiaochun Han

“…We systematically searched for studies that applied machine learning algorithms to MRI data for diagnosing PD with mild cognitive impairment (PD-MCI). …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Notably, among different BRCA molecular sub-types, Hormone Receptor negative (HR-) BRCA cases, especially Basal-like BRCA sub-types, lack estrogen and progesterone hormone receptors and they exhibit a higher tumor growth rate compared to HR+ cases. …”
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Towards Reinforced Brain Tumor Segmentation on MRI Images Based on Temperature Changes on Pathologic Area by Abdelmajid Bousselham, Omar Bouattane, Mohamed Youssfi, Abdelhadi Raihani

“…We conclude that tumor contours delineation based on tumor temperature changes can be exploited to reinforce and enhance segmentation algorithms in MRI diagnostic.…”
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Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma by Guoyin Li, Yukui Zhao, Yubo He, Zhaoqiang Qian, Yiwen Liu, Xiaoyan Li, Lili Li, Zhiqiang Liu

“…CIBERSORT and ESTIMATE algorithms were employed to evaluate the infiltration of immune cells. …”
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STUDY OF PREDICTION AND CLASSIFICATION MODELS IN THE PROBLEMS OF DIABETES AMONG PATIENTS WITH A STROKE IN DIFFERENT LIVING CONDITIONS by Nural Huliiev, Maksym Peretiaha, Artem Khovrat, Denys Teslenko, Alexei Nazarov

“…The article solves the problem of a multi-criteria task of choosing the best algorithm for predicting the occurrence of a disease. …”
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Aperiodic activity as a biomarker of seizures and neuromodulation by David Satzer, Lesley C. Kaye, Steven G. Ojemann, Daniel R. Kramer, John A. Thompson

“…Recordings containing clinician-annotated seizures, stimulation triggered by device-detected interictal epileptiform activity (IEA), and stimulation-free interictal periods were analyzed. …”
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Using Machine Learning and Nationwide Population-Based Data to Unravel Predictors of Treated Depression in Farmers by Pascal Petit, Vincent Bonneterre, Nicolas Vuillerme

“…Farmers are exposed to numerous stressors that can negatively impact their mental health, leading to conditions such as depression. …”
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Predicting the occurrence of probable sarcopenia in middle-aged and elderly patients with coronary artery disease: development and validation of a clinical model by Xiaolan Sun, Jia Xu, Feier Chen, Haiyan Lei, Wei Chen, Fang Ding, Xueping Li

“…Abstract The objective of this research was to identify the factors contributing to the decline in handgrip strength among middle-aged and elderly individuals with this condition. In addition, an algorithmic model for the detection of probable sarcopenia will be developed. …”
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Clinical Phenotypes of Patients with Anti-DFS70/LEDGF Antibodies in a Routine ANA Referral Cohort by Makoto Miyara, Roger Albesa, Jean-Luc Charuel, Mohamed El Amri, Marvin J. Fritzler, Pascale Ghillani-Dalbin, Zahir Amoura, Lucile Musset, Michael Mahler

“…Only 5/91 (5.5%) patients with anti-DFS70 antibodies had SARD and their sera were negative on the ANA Screen ELISA. Conclusion. Although anti-DFS70 antibodies cannot exclude the presence of SARD, the likelihood is significantly lower than in patients with other IIF patterns and should be included in test algorithms for ANA testing.…”
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Correlating gene expression levels with transcription factor binding sites facilitates identification of key transcription factors from transcriptome data by Tinghua Huang, Siqi Niu, Fanghong Zhang, Binyu Wang, Jianwu Wang, Guoping Liu, Min Yao

“…ED was identified as the optimal method for creating a ranked gene list from filtered expression data, which can address the “unable to detect negative correlation” fallacy presented by other methods. …”
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The Specific Features of the Pathogenesis and Correction of Critical Conditions in Obstetric Care by Yu. S. Podolsky

“…Water sectoral disorders were detected in three steps: on days 1, 3, and 5; these were identified in four steps in case of eclamptic coma (EC), regional anesthesia, and impaired oxygen status. …”
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"Proof-of-concept" evaluation of an automated sputum smear microscopy system for tuberculosis diagnosis. by James J Lewis, Violet N Chihota, Minty van der Meulen, P Bernard Fourie, Katherine L Fielding, Alison D Grant, Susan E Dorman, Gavin J Churchyard

“…<h4>Background</h4>"TBDx" is an innovative smear microscopy system that automatically loads slides onto a microscope, focuses and digitally captures images and then classifies smears as positive or negative using computerised algorithms.<h4>Objectives</h4>To determine the diagnostic accuracy of TBDx, using culture as the gold standard, and compare this to a microscopist's diagnostic performance.…”
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Klasifikasi Multilabel Pada Gaya Belajar Siswa Sekolah Dasar Menggunakan Algoritma Machine Learning by I Kadek Nicko Ananda, Ni Putu Novita Puspa Dewi, Ni Wayan Marti, Luh Joni Erawati Dewi

“…A recall value of 99% indicates that the model is able to detect almost all positive labels correctly, and an F1-score of 98% indicates that the model has excellent and balanced performance, without bias against both positive and negative label predictions. …”
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The Relationship Between Novel Inflammatory Markers and Serum 25‐Hydroxyvitamin D Among US Adults by Hang Zhao, Yangyang Zhao, Yini Fang, Weibang Zhou, Wenjing Zhang, Jiecheng Peng

“…To further explore the relationship between the two, we applied smooth curve fittings and generalized additive models. Upon detecting nonlinear relationships, we used a recursive algorithm to pinpoint the inflection point. …”
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Sentiment analysis for deepfake X posts using novel transfer learning based word embedding and hybrid LGR approach by Madiha Khalid, Muhammad Faheem Mushtaq, Urooj Akram, Mejdl Safran, Sultan Alfarhood, Imran Ashraf

“…The proposed approach helps detect and prevent the spread of deepfake content, keeping people and organizations safe from its negative effects. …”
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Wellcounter: Automated high‐throughput phenotyping for aquatic microinvertebrates by Claus‐Peter Stelzer, Dominique Groffman

“…For those interested in developing image analysis algorithms, we provide large annotated datasets, including high‐resolution movies and images with known quantities and positions of specimens. …”
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Efficient Deep Learning Models Revolutionize Doctor&#x2019;s Training for Point-of-Care Ultrasound by Hsin-Hung Chou, Yi-Chung Chang, Wan-Ching Lien, Lung-Chun Lin, Xing-Zheng Lin, Ting-En Hsu, Yueh-Ping Liu, Li Liu, Yen-Ting Chan, Feng-Sen Kuan

“…This study aims to develop a deep learning (DL) model for detecting and localizing PCE and to investigate the learning efficacy of using this model as an adjunct in PoCUS training. …”
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