Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study by Jessica Rogan, Joseph Firth, Sandra Bucci

“…Passive sensing can enhance assessment objectivity, but it raises concerns about privacy, data storage, consent and data accuracy. Machine learning algorithms may increase awareness of support needs, yet lack context, risking misdiagnosis. …”
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The Significance of Cellular Senescence Hub Genes in the Diagnosis and Subtype Classification of a Comprehensive Database of Gene Expression in Intervertebral Disc Degeneration by Fei Liu, Silong Gao, Ji Yin, Chao Song, Yongliang Mei, Zhaoqiang Wang, Zongchao Liu

“…Conclusion In summary, CSRGs play an important role in the pathogenesis of IVDD, and our study of the hub gene cluster may guide future therapeutic strategies for IVDD.…”
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Use of filtration and electricity analogy in simulation of underflooding protection in urban construction by V. I. Sologaev

“…An additional feature of joint modelling in a porous medium of water filtration and electroosmosis is that the mass of the water-resistant part of the soil and its part related to the dielectric may not coincide. This complexity of the model is overcome by dividing it into modules, which can then be combined in compliance with the balance principle, stitching modules along the boundaries. …”
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A Transfer Learning-Based Framework for Classifying Lymph Node Metastasis in Prostate Cancer Patients by Suryadipto Sarkar, Teresa Wu, Matthew Harwood, Alvin C. Silva

“…Earlier research focused on implementing texture algorithms to extract imaging features used in classification models. …”
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Integrative analysis of multi-omics data identified PLG as key gene related to Anoikis resistance and immune phenotypes in hepatocellular carcinoma by Xueyan Wang, Lei Gao, Haiyuan Li, Yanling Ma, Bofang Wang, Baohong Gu, Xuemei Li, Lin Xiang, Yuping Bai, Chenhui Ma, Hao Chen

“…This study provides novel insights into the molecular subtypes of HCC through the application of robust clustering algorithms based on multi-omics data. The constructed CMLS serves as a valuable tool for early prognostic prediction and for screening potential drug candidates that may enhance the efficacy of immunotherapy, thereby establishing a foundation for personalized treatment strategies in HCC. …”
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Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS by Ling Gao, Tingting Liu, Xiaoyan Li

“…The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. …”
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The real-world analysis of adverse events with azacitidine: a pharmacovigilance study based on the FAERS and WHO-VigiAccess databases by Zhaorui Wang, Linlin Guo, Youfu He, Baiquan Zhang, Yang Wang, Juan Ding

“…However, adverse events (AEs) associated with azacitidine are mainly reported in clinical trials, with limited real-world evidence. …”
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Analysis and Validation of Autophagy-Related Gene Biomarkers and Immune Cell Infiltration Characteristic in Bronchopulmonary Dysplasia by Integrating Bioinformatics and Machine Lea... by Xiao S, Ding Y, Du C, Lv Y, Yang S, Zheng Q, Wang Z, Zheng Q, Huang M, Xiao Q, Ren Z, Bi G, Yang J

“…Subsequently, the hub genes were identified by Lasso and Cytoscape with three machine-learning algorithms (MCC, Degree and MCODE). In addition, hub genes were validated with ROC, single-cell sequence and IHC in hyperoxia mice. …”
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Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare by Jeremy Y. Ng, Holger Cramer, Myeong Soo Lee, David Moher

“…This integration of TCIM and AI introduces exciting opportunities but also noteworthy challenges. AI may augment TCIM by assisting in early disease detection, providing personalized treatment plans, predicting health trends, and enhancing patient engagement. …”
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IDENTIFICATION OF SMALL LAKES IN KAZAKHSTAN USING REMOTE SENSING DATA by Akmaral Tolepbayeva, Dinara Abiyeva, Roza Karagulova, Aigerim Tanbayeva, Zhanerke Sharapkhanova

“…However, challenges such as dense vegetation, high salinity, and the color of shallow lake bottoms led to some classification errors, highlighting the need for further refinement of automated algorithms. As a result, a list of small lakes in Kazakhstan with a surface area from 1 to 10 km2 was identified. …”
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Real-World Analysis of HRD Assay Variability in High-Grade Serous Ovarian Cancer: Impacts of BRCA1/2 Mutation Subtypes on HRD Assessment by Giovanni Luca Scaglione, Valentina Lombardo, Maurizio Polano, Giuseppa Scandurra, Angela Pettinato, Corrado Giunta, Rosario Iemmolo, Paolo Scollo, Ettore D. Capoluongo

“…Recent findings indicate that not all <i>BRCA1/2</i> mutations determine the magnitude of HRD and that some patients carrying <i>BRCA1/2</i> mutations may exhibit indeterminate or even negative HRD scores. …”
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Literature Review of Prognostic Factors in Secondary Generalized Peritonitis by Valerii Luțenco, Adrian Beznea, Raul Mihailov, George Țocu, Verginia Luțenco, Oana Mariana Mihailov, Mihaela Patriciu, Grigore Pascaru, Liliana Baroiu

“…Emerging evidence suggests that machine learning algorithms may improve early risk stratification and individualized outcome prediction when integrated with conventional scoring systems. …”
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Inflammation-Mediated Regulation of MicroRNA Expression in Transplanted Pancreatic Islets by Valia Bravo-Egana, Samuel Rosero, Dagmar Klein, Zhijie Jiang, Nancy Vargas, Nicholas Tsinoremas, Marco Doni, Michele Podetta, Camillo Ricordi, R. Damaris Molano, Antonello Pileggi, Ricardo L. Pastori

“…The association between these miRNAs and mRNA target-predicting algorithms in genome-wide RNA studies of β-cell inflammation identified 238 potential miRNA gene targets. …”
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Using Neural Networks to Automate the Identification of Brightest Cluster Galaxies in Large Surveys by Patrick Janulewicz, Tracy M. A. Webb, Laurence Perreault-Levasseur

“…Though some cluster finding techniques identify the position of the BCG and use it as the cluster center, other techniques may not automatically include these coordinates. …”
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Investigating the truncated fractional telegraph equation in engineering: Solitary wave solutions, chaotic and sensitivity analysis by Usman Younas, Jan Muhammad, Muhammad Amin S. Murad, D.K. Almutairi, Aziz Khan, Thabet Abdeljawad

“…The results obtained may enhance the understanding of nonlinear system dynamics and validate current methods, significantly contributing to the fields of nonlinear science and wave phenomena. …”
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Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review by Natalie S Blencowe, Neil J Smart, George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway

“…Benefits include applications to improve health systems, such as rapid and accurate interpretation of medical images. This may improve the performance of diagnostic, prognostic and management decisions. …”
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In silico analysis of atrial fibrillation and hypertension mechanism of action secondary to ibrutinib/acalabrutinib in chronic lymphocytic leukemia by Raúl Córdoba, Antoni Bayés-Genís, Ana Muntañola, Dolors Colomer, Jorge Castro, Carolina Leiva, Esther Álvarez, Eduardo Zatarain-Nicolas

“…These adverse events seem to be derived from off-targets rather than BTK inhibition. Machine learning algorithms were applied to identify targets likely to trigger AF and hypertension in simulated CLL patients receiving acalabrutinib or ibrutinib. …”
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Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…Existing GPM techniques often depend on parametric models, which may fail to capture the intricate patterns of groundwater distribution or adapt to varying data complexities. …”
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Harnessing Artificial Intelligence for the Diagnosis, Treatment and Research of Multiple Sclerosis by Manisha S. Patil, Linda Y. Lin, Rachel K. Ford, Elizaveta J. James, Stella Morton, Felix Marsh-Wakefield, Simon Hawke, Georges E. Grau

“…AI can help identify subtle changes in the brain and spinal cord that may be missed by human clinicians, leading to earlier diagnosis and more personalised treatment plans. …”
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An Exploration on Aperiodic Activities and Transient Oscillations During Semantic Processing: A Study With Wearable MEG by Xiaoyu Liang, Yuyu Ma, Ruonan Wang, Huanqi Wu, Changzeng Liu, Fuzhi Cao, Nan An, Min Xiang, Yueyang Zhai, Xiaolin Ning

“…In this study, recently developed algorithms were employed to parameterize the time-frequency characteristics of neural activities captured with optically pumped magnetometers-based wearable Magnetoencephalography from participants engaged in a Chinese semantic-based task. …”
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