A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation by Dong Miao, Ying Zhao, Xue Ren, Meng Dou, Yu Yao, Yiran Xu, Yingchao Cui, Ailian Liu

“…To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver function.This research presents a novel approach to automating liver segmentation by identifying seven key anatomical landmarks using portal venous phase images from contrast-enhanced magnetic resonance imaging (CE-MRI). …”
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Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume by Ting-Wen Sheng, Djeane Debora Onthoni, Pushpanjali Gupta, Tsong-Hai Lee, Prasan Kumar Sahoo

“…<b>Background:</b> Total Kidney Volume (TKV) is widely used globally to predict the progressive loss of renal function in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). …”
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Environmental enrichment reverses noise induced impairments in learning and memory associated with the hippocampus in female rats by Yutian Sun, Pengying An, Yongjian Cai, Wenjing Yang, Yue Fang, Hui Liu, Guimin Zhang, Ye Shan, Jie Wang, Yifan Zhang, Xiaoming Zhou

“…Abstract Environmental enrichment (EE) has positive effects on brain function and behavior in both healthy and behaviorally impaired animals. …”
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Open-access ultrasonic diaphragm dataset and an automatic diaphragm measurement using deep learning network by Zhifei Li, Lin Mao, Fan Jia, Shaohui Zhang, Cuiping Han, Shuiqiao Fu, Yueying Zheng, Yonghua Chu, Zuobing Chen, Daming Wang, Huilong Duan, Yinfei Zheng

“…Abstract Background The assessment of diaphragm function is crucial for effective clinical management and the prevention of complications associated with diaphragmatic dysfunction. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

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Deep Learning dengan Teknik Early Stopping untuk Mendeteksi Malware pada Perangkat IoT by Iwang Moeslem Andika Surya, Triawan Adi Cahyanto, Lutfi Ali Muharom

“…This approach utilizes machine learning techniques and intense learning to identify and mitigate cyber threats. …”
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Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease by Ruijie Zhao, Yun Wang, Jiaru Wang, Zixing Wang, Ran Xiao, Ying Ming, Sirong Piao, Jinhua Wang, Lan Song, Yinghao Xu, Zhuangfei Ma, Peilin Fan, Xin Sui, Wei Song

“…Abstract Aim Timely intervention of interstitial lung disease (ILD) was promising for attenuating the lung function decline and improving clinical outcomes. The prone position HRCT is essential for early diagnosis of ILD, but limited by its high radiation exposure. …”
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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

“…The optimal algorithm achieves unbiased cloud detection across multiple surfaces by adjusting the output threshold of the mapping function, allowing for cloud detection results with varying confidence levels as required. …”
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Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients by Yunjie Zhang, Songjian Tong, Junhui Yang, Jiawei Lin, Yifan Kong, Deyu Lu, Yan Chen, Yingchao Li, Linfeng Xu, Xiuyan Kong, Guoqing Zhu, Hao Zhang, Pixu Liu, Zhijie Yu, Jinglin Xia

“…SHAP interpretability revealed tumor burden and hepatic function markers as key determinants of TACE resistance. …”
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Multi-Objective Optimization of Machine Learning-Based Nonlinear Equalizers for Digital Coherent Optical Interconnects by Lucas C. Dantas, Hildo Guillardi Junior, Plinio Dester, Rafael A. Penchel, Jose Augusto de Oliveira, Marcelo L. F. Abbade, Leandra I. Abreu, Jinlong Wei, Ivan Aldaya

“…Machine learning-based equalizers offer reduced complexity and improved adaptability. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…This study aimed to develop and validate a diagnostic model for AAE using routine blood parameters through machine learning techniques. Methods: We developed a machine learning-based diagnostic model using routine blood test parameters. …”
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Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank by Wei Xu, Ines Mesa-Eguiagaray, David M. Morris, Chengjia Wang, Calum D. Gray, Samuel Sjöström, Giorgos Papanastasiou, Sammy Badr, Julien Paccou, Xue Li, Paul R. H. J. Timmers, Maria Timofeeva, Susan M. Farrington, Malcolm G. Dunlop, Scott I. Semple, Tom MacGillivray, Evropi Theodoratou, William P. Cawthorn

“…Abstract Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. …”
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Design and Development of Information Content of an Open Online School for Foreign Citizens in Russian by N. I. Gorodetskaya, I. E. Belotserkovskaya, T. V. Tumanova, N. B. Sherbakova

“…The concepts of continuing education, the principles of adult education, approaches to the use of e-learning, distance learning technologies, principles and approaches to the development and implementation of mass online-courses are the theoretical basis of our paper. …”
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Debiasing Structure Function Estimates from Sparse Time Series of the Solar Wind: A Data-driven Approach by Daniel Wrench, Tulasi N. Parashar

“…Structure functions (SFs), which quantify the moments of increments of a stochastic process, are essential complementary statistics to power spectra for analyzing the self-similar behavior of a time series. …”
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Role of Toll-Like Receptors in Actuating Stem/Progenitor Cell Repair Mechanisms: Different Functions in Different Cells by Fabio Sallustio, Claudia Curci, Alessandra Stasi, Giuseppe De Palma, Chiara Divella, Roberto Gramignoli, Giuseppe Castellano, Anna Gallone, Loreto Gesualdo

“…In this review, we analyze the many different functions that the TLRs assume in SCs, pointing out that they can have different effects, depending on the background and on the kind of ligands that they recognize. …”
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Torque Ripple Minimization for Switched Reluctance Motor Drives Based on Harris Hawks–Radial Basis Function Approximation by Jackson Oloo, Szamel Laszlo

“…This work combines the benefits of Harris Hawks Optimization (HHO) and Radial Basis Functions (RBFs) to search and estimate optimal switching angles. …”
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Functional characterization of DPP4 and FcRn as receptor and coreceptor for classical human astroviruses in Caco-2 cells. by Catalina Aguilera-Flores, María Del Pilar Valencia-Morales, Tomás López, Joaquín Moreno-Contreras, Adam Lentz, Marco A Espinoza, Rebecca M DuBois, Susana López, Carlos F Arias

“…However, the precise roles of FcRn and DPP4 during HAstV infection are unknown. To learn about their function, we used FcRn-knockout (KO), DPP4-KO, and FcRn/DPP4 double-KO Caco-2 cells generated via CRISPR/Cas9. …”
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How the families of the victims of suicide through self-incineration function before and after the event — a qualitative assessmen by L.H. Mabuza, G.A. Ogunbanjo, R.N. Malete

“…The focus was on the surviving family members, in order to learn about the family dynamics before and after the events, and how the family dealt with the event. …”
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Abnormal Gray Matter Volume and Functional Connectivity in Parkinson’s Disease with Rapid Eye Movement Sleep Behavior Disorder by Xu Jiang, Zhuang Wu, Min Zhong, Bo Shen, Jun Zhu, Yang Pan, Jun Yan, Wenbin Zhang, Pingyi Xu, Chaoyong Xiao, Li Zhang

“…Twenty-four polysomnography-confirmed patients with PD-RBD, 26 patients with PD-nRBD, and 26 healthy controls were enrolled. Structural and functional patterns were analyzed based on voxel-based morphometry and seed-based functional connectivity (FC). …”
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TEMPO: Timestep Explanations for Modeling Preferences in Online Preference-Based RL by Jakob Karlaus, Friedhelm Schwenker

“…Our key technical innovation is a training approach that incorporates these explanations using a novel loss function combining reward learning, saliency-based explanations, and structural regularization. …”
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