Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

“…In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate by extensive simulations that PIXANT is reliable, robust and highly resource-efficient. …”
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Unsupervised Clustering of Cell Populations in Germinal Centers Using Multiplexed Immunofluorescence by Simon Burgermeister, Michail Orfanakis, Spiros Georgakis, Cloe Brenna, Helen Lindsay, Craig Fenwick, Giuseppe Pantaleo, Raphael Gottardo, Constantinos Petrovas

“…We evaluate multiple clustering algorithms and find that k-means clustering provides the most effective separation of distinct cell subsets. …”
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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…This study aims to evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases and explore their potential impact on clinical practice. …”
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Data transfers for nuclear reactor multiphysics studies using the MOOSE framework by Guillaume L. Giudicelli, Guillaume L. Giudicelli, Fande Kong, Roy Stogner, Logan Harbour, Derek Gaston, Alexander Lindsay, Zachary Prince, Lise Charlot, Stefano Terlizzi, Mahmoud Eltawila, April Novak

“…Advanced nuclear reactor cores are governed by multiple physical phenomena which should be all be resolved, and the coupling of these physics would also need to be resolved spatially in a high-fidelity approach, while lower fidelity may leverage integrated quantities for the coupling instead. …”
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Small Molecules in the Treatment of Acute Severe Ulcerative Colitis: A Review of Current Evidence by Raffaele Pellegrino, Giuseppe Imperio, Ilaria De Costanzo, Michele Izzo, Fabio Landa, Assunta Tambaro, Antonietta Gerarda Gravina, Alessandro Federico

“…Despite this approach, a significant proportion of patients fail to respond to either corticosteroids or infliximab and may require alternative therapeutic options if there is no urgent surgical necessity. …”
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A Multiscale Convolution SAR Image Target Recognition Method Based on Complex-Valued Neural Networks by Guangyu Hou, Zhihui Xin, Guisheng Liao, Penghui Huang, Yuhao Huang, Rui Zou

“…Many deep learning algorithms rely solely on amplitude information, ignoring phase information, which may result in the loss of information in the original complex-valued SAR image and suboptimal performance. …”
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Target repositioning using multi-layer networks and machine learning: The case of prostate cancer by Milan Picard, Marie-Pier Scott-Boyer, Antoine Bodein, Mickaël Leclercq, Julien Prunier, Olivier Périn, Arnaud Droit

“…However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. …”
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A Dynamic Spike Sorter for Multiscale Nanoelectrode Array Recordings by Shivani Shukla, Callum Walsh, Shashank Bansal, Johannes Leugering, Abhinav Uppal, Vikrant Jaltare, Gert Cauwenberghs, Sreekanth H. Chalasani, Zeinab Jahed

“…Advanced sorting algorithms tailored for nanoelectrode array recordings are essential for unlocking the full potential of next generation, high throughput neuroelectronic devices and achieving a deeper understanding of neuronal dynamics.…”
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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

“…Developmental coordination disorder (DCD) is a motor learning disability with a prevalence of 5%-6% in school-aged children, which may seriously affect the physical and mental health of affected children. …”
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REST Network: An Ensemble Deep Learning Approach for EV Charging Load Forecasting in Artificial Port Supply Chains by Elham Abdullah Alghamdi, Monagi Hassan Alkinani, Abdulwahab Ali Almazroi, Mohammed Alqarni, Eman Ali Aldhahri, Nasir Ayub

“…Traditional forecasting algorithms can fail to address logistics’ complicated, variable charge patterns and uneven data. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…It is divided into two main types: acute, which stems from early cell growth ab- normalities and involves rapid immature cell proliferation, and chronic, which progresses more slowly due to a blockage in the later stages of the cell life cycle. …”
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Enhancing forest biodiversity indicators in inventories through harmonized protocols by Moreno-Fernández D, Breidenbach J, Cañellas I, Chirici G, D’Amico G, Ferretti M, Giannetti F, Puliti S, Schnell S, Shackleton R, Skudnik M, Alberdi I

“…., stand structure and deadwood), which may not provide sufficient information on other aspects of the current forest biodiversity status. …”
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Study of the interval width of features for improving forecasting efficiency of the transport flow intensity by I. N. Pugachev, N. G. Sheshera, D. Yе. Grigorov

“…Logicaland statistical validity of the selection automation of interval rages are the main feature of this method. This is necessary not only for grouping features, but also for increasing their value in a joint analysis. …”
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Optimizing image capture for low-light widefield quantitative fluorescence microscopy by Zane Peterkovic, Avinash Upadhya, Christopher Perrella, Admir Bajraktarevic, Ramses E. Bautista Gonzalez, Megan Lim, Kylie R. Dunning, Kishan Dholakia

“…In such studies, it is important to reduce the intensity of illumination to reduce adverse effects such as photobleaching and phototoxicity that may perturb the biological system under study. The challenge when minimizing illumination is to maintain image quality that reflects the underlying biology and can be used for quantitative measurements. …”
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Prediction and Identification of Potential Immunodominant Epitopes in Glycoproteins B, C, E, G, and I of Herpes Simplex Virus Type 2 by Mingjie Pan, Xingsheng Wang, Jianmin Liao, Dengke Yin, Suqin Li, Ying Pan, Yao Wang, Guangyan Xie, Shumin Zhang, Yuexi Li

“…These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2.…”
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Cathepsin C correlates with M2 macrophage infiltration and regulates the tumor growth and metastasis in non-small cell lung cancer by Xiaoxia Tong, Ting Zhu, Li Ma, Xiaohu Yang, Chenghui Li, Yibing Liu, Xuan Qin, Yanguang Ding, Hongwei Xia, Yonglei Liu

“…CTSC overexpression in NSCLC cells showed the opposite effects. Targeting CTSC may provide a promising treatment strategy for NSCLC patients.…”
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An intelligible AI-driven decision support system for poststroke mobility assessment by Jin Cheng Liaw, Dominik Raab, Malte Weber, Mario Siebler, Harald Hefter, Dörte Zietz, Marcus Jäger, Andrés Kecskeméthy, Francisco Geu Flores

“…Synergistic interactions between system, and experts via the computed key features may improve quality in diagnosis and objectify therapeutic targets. …”
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A Practical Implementation of Post-Quantum Cryptography for Secure Wireless Communication by Babatunde Ojetunde, Takuya Kurihara, Kazuto Yano, Toshikazu Sakano, Hiroyuki Yokoyama

“…On the other hand, PQC algorithms come with complexity and long processing times, which may impact the quality of service (QoS) of many applications. …”
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Obtaining the Highest Quality from a Low-Cost Mobile Scanner: A Comparison of Several Pipelines with a New Scanning Device by Marek Hrdina, Juan Alberto Molina-Valero, Karel Kuželka, Shinichi Tatsumi, Keiji Yamaguchi, Zlatica Melichová, Martin Mokroš, Peter Surový

“…Given the growing availability of 3D-based forest inventory algorithms, a selection of such processing pipelines was used to assess the practical potential of the scanning devices. …”
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Machine Learning Introduces Electrophysiology Assessment as the Best Predictor for the Recovery Prognosis of Spinal Cord Injury Patients for Personalized Rehabilitation Approaches by Dionysia Chrysanthakopoulou, Charalampos Matzaroglou, Eftychia Trachani, Constantinos Koutsojannis

“…The strong correlation between evoked potentials (EPs) and American Spinal Injury Association (ASIA) scores in individuals with spinal cord injury (SCI) suggests that EPs may serve as reliable predictive markers for rehabilitation progress. …”
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