Inclusion of non-medical interventions in model-based economic evaluations for tuberculosis: A scoping review. by Lauren C Ramsay, Marina Richardson, Rafael N Miranda, Marian Hassan, Sarah K Brode, Elizabeth Rea, Beate Sander

“…As a secondary objective, this review aims to characterize key features of existing economic evaluations of medical and non-medical interventions.…”
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AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review by Sandra López Gordo, Elena Ramirez-Maldonado, Maria Teresa Fernandez-Planas, Ernest Bombuy, Robert Memba, Rosa Jorba

“…These models integrate clinical, laboratory, and imaging data, including radiomics features, and are useful in diagnostic and prognostic accuracy in AP. …”
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Differential late-stage face processing in autism: a magnetoencephalographic study of fusiform gyrus activation by Darko Sarovic, Justin Schneiderman, Sebastian Lundström, Bushra Riaz, Elena Orekhova, Sheraz Khan, Christopher Gillberg

“…The fusiform face area was identified using a face localizer for each participant, and the cortical activation pattern was normalized onto an average brain for subsequent analysis. Results Early post-stimulus activation amplitudes (before 100–200 ms) indicated differentiation between stimuli containing fundamental facial features and non-face objects in both groups. …”
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Diabetes and dementia: current data by N.V. Pashkovska, V.M. Pashkovskyy

“…Diagnosis also includes neuroimaging, cerebral hemodynamics analysis, and cerebrospinal fluid biomarker testing (beta-amyloid, tau protein), while PET scans for amyloid and tau, along with neuronal damage markers, are promising for early detection and staging of the disease. …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Furthermore, a novel Attention-augmented Spatial-Temporal Graph Convolutional Network (AST-GCN) is developed for reliably identifying the action in each frame, enabling accurate computation of key kinematic features for fall risk prediction. Experimental evaluations on a dataset of 450 FSTS test videos demonstrate the high performance of <sc>FRAVM</sc>, with detection accuracy, F1 score, and ROC-AUC achieving 88.64%, 88.58%, and 98.86%, respectively. …”
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Severe Acute Respiratory Syndrome Coronavirus 2 Variant Infection Dynamics and Pathogenesis in Transgenic K18-h<i>ACE2</i> and Inbred Immunocompetent C57BL/6J Mice by Hongwei Liu, Brianna M. Ramirez, Talia S. Wong, Christopher M. Weiss, Kevin C. K. Lloyd, Qizhi Gong, Lark L. Coffey

“…SARS-CoV-2 nucleoprotein was detected, and interstitial pneumonia of varying severity was observed in K18 mice infected with all variants. …”
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Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite by Hassan Rasoulzadeh, Hossein Azarpira, Mojtaba Pourakbar, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Prior to applying machine learning models, preprocessing steps were performed, including normalization using Min–Max Scaling to confine all features within the [0,1] range, outlier detection and removal of anomalous values, correlation analysis to avoid redundancy and multicollinearity, and data splitting into training and testing sets at an 80:20 ratio, along with K-fold cross-validation (k = 5) for robust model evaluation. …”
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Number of intraepithelial lymphocytes and presence of a subepithelial band in normal colonic mucosa differs according to stainings and evaluation method by Anne-Marie Kanstrup Fiehn, Peter Johan Heiberg Engel, Ulla Engel, Dea Natalie Munch Jepsen, Thomas Blixt, Julie Rasmussen, Signe Wildt, Wojciech Cebula, Andreea-Raluca Diac, Lars Kristian Munck

“…As the histology of normal intestinal mucosa vary, discriminating subtle features of MC from normal tissue can be challenging and therefore auxiliary stainings are increasingly used. …”
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Current situation in relation to parasites and measures of struggle against them in Russia and cis countries (based on materials of coordinating reports) by A. V. USPENSKY, E. I. MALAHOVA, T. A. YERSHOVA

“…Features of parasitosis course in carnivorous in Black Earth and Non-Black Earth zones, Krasnodar Krai and Altai are studied. …”
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Unveiling the complexity of Schimmelpenning–Feuerstein–Mims syndrome: A comprehensive case study by Guillermo Raul Vera-Duarte, Ruth Eskenazi-Betech, Isabel De la Fuente-Batta, David Carreño-Bolaños, Oscar F. Chacón-Camacho, Juan C. Zenteno, Enrique O. Graue-Hernandez

“…Purpose: The purpose of this study was to report the comprehensively examined patient exhibiting oculocutaneous clinical features of Schimmelpenning–Feuerstein–Mims syndrome (SFMS). …”
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Mitral valve prolapse—arrhythmic faces of the valve disease by Maria Możdżan, Monika Możdżan, Iwona Duraj, Zofia Możdżan, Mateusz Staciwa, Marlena Broncel, Karina Wierzbowska-Drabik

“…Cardiac magnetic resonance (CMR) imaging and speckle tracking echocardiography are new tools showing significant potential for detection of malignant features of AMVP. This paper presents various data coming from electrocardiography (ECG) analysis, echocardiography, and other imaging techniques as well as compilation of the recent studies on the subject of MVP.…”
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The Desmoid Dilemma: Challenges and Opportunities in Assessing Tumor Burden and Therapeutic Response by Yu-Cherng Chang, Bryan Nixon, Felipe Souza, Fabiano Nassar Cardoso, Etan Dayan, Erik J. Geiger, Andrew Rosenberg, Gina D’Amato, Ty Subhawong

“…Radiomics and artificial intelligence approaches may enhance quantitative analysis by extracting and correlating complex imaging features with biological behavior. …”
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Toward Characterizing Dark Matter Subhalo Perturbations in Stellar Streams with Graph Neural Networks by Peter Xiangyuan Ma, Keir K. Rogers, Ting S. Li, Renée Hložek, Jeremy J. Webb, Ruth Huang, Julian Meunier

“…The phase space of stellar streams is proposed to detect dark substructure in the Milky Way through the perturbations created by passing subhalos—and thus is a powerful test of the cold dark matter paradigm and its alternatives. …”
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Trajectory of plasma lipidome associated with the risk of late-onset Alzheimer's disease: a longitudinal cohort studyResearch in context by Tingting Wang, Matthias Arnold, Kevin Huynh, Patrick Weinisch, Corey Giles, Natalie A. Mellett, Thy Duong, Bharadwaj Marella, Kwangsik Nho, Alysha De Livera, Xianlin Han, Colette Blach, Chenglong Yu, John J. McNeil, Paul Lacaze, Andrew J. Saykin, Gabi Kastenmüller, Peter J. Meikle, Rima Kaddurah-Daouk

“…Findings: Longitudinal analysis identified significant associations between the change in ether lipid species (including alkylphosphatidylcholine, alkenylphosphatidylcholine, lysoalkylphosphatidylcholine, and lysoalkenylphosphatidylcholine) and AD dementia conversion. …”
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Non-Invasive Prenatal Screening for Down Syndrome: A Review of Mass-Spectrometry-Based Approaches by Răzvan Lucian Jurca, Ioana-Ecaterina Pralea, Maria Iacobescu, Iulia Rus, Cristina-Adela Iuga, Florin Stamatian

“…Additionally, pathway analysis is carried out to explore the biological pathways that these molecules are involved in and how they relate to the clinical features of the syndrome. …”
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A hybrid variational mode decomposition framework for enhanced cardiac output estimation using impedance cardiography by Priya Darshini Kumari, Ksh Milan Singh, Zefree Lazarus Mayaluri, Prabodh Kumar Sahoo, Satyabrata Lenka, Ganapati Panda, Sujeevan Kumar Agir

“…These findings confirm that the proposed method outperforms state-of-the-art alternatives in preserving both signal fidelity and clinically significant features under both stationary and non-stationary noise. …”
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STABILITY OF DEVELOPMENT OF FUTURE PROFESSIONALS’ EMOTIONAL INTELLIGENCE by A. M. Beloborodov, E. E. Symaniuk

“…Gilford’s Social Intelligence Test and also the authors’ set of toolkits (tasks for recognition of facial expression and detection of the active dictionary of emotions) were applied.Results and scientific novelty. …”
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Building digital histology models of transcriptional tumor programs with generative deep learning for pathology-based precision medicine by Hanna M. Hieromnimon, James Dolezal, Kristina Doytcheva, Frederick M. Howard, Sara Kochanny, Zhenyu Zhang, Robert L. Grossman, Kevin Tanager, Cindy Wang, Jakob Nikolas Kather, Evgeny Izumchenko, Nicole A. Cipriani, Elana J. Fertig, Alexander T. Pearson, Samantha J. Riesenfeld

“…Methods Our approach detects expression of transcriptional programs from tumor histology and interprets the image features supporting program detection. …”
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Structure-threshold relationship in food aroma molecules: Insights from S-curve method, molecular docking, and dynamics simulations by Jingtao Wang, Chenglei Zhang, Jiancai Qian, Shan Wang, Wu Fan, Qingzhao Shi, Jian Mao, Jianping Xie, Qidong Zhang, Guobi Chai

“…Molecular dynamics simulations identified hydrogen bond stability and receptor conformational flexibility as threshold determinants, exhibiting more stable hydrogen bonds and greater conformational flexibility displayed lower detection thresholds. These findings establish a predictive framework linking molecular structural features to odor thresholds while elucidating ligand-receptor interaction mechanisms, providing theoretical foundations for rational flavor design and sensory modulation strategies.…”
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Prevalence and Structure of the Malocclusions in Children from Boarding Schools by Smolyar N., Fuhr N.

“…That’s why their early detection is very important in children at the stage of temporary dentition, when dentoalveolar system is under constant growth. …”
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