Frailty prediction in patients with chronic digestive system diseases: based on multi-task learning model by Sihan Hu, Xiaochuan Guo, Xiaobao Wang, Zixiang Jin, Chenyang Zhou, Lang Tu, Zhoulong Shi, Weiyi Ao, Xin Zhang, Jay Zheng, Xuezhi Zhang, Hui Ye

“…Utilizing the Multi-Gate Mixture-of-Experts (MMoE) framework, we built and evaluated five models: Tab Transformer, Convolutional Neural Network (CNN), Deep Neural Network (DNN), Extreme Gradient Boosting (XGBoost) and Random Forest (RF). …”
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Lung volume assessment for mean dark-field coefficient calculation using different determination methods by Florian T. Gassert, Jule Heuchert, Rafael Schick, Henriette Bast, Theresa Urban, Tina Dorosti, Gregor S. Zimmermann, Sebastian Ziegelmayer, Alexander W. Marka, Markus Graf, Marcus R. Makowski, Daniela Pfeiffer, Franz Pfeiffer

“…Radiography-based methods simplify workflows and minimize biases, making them most suitable. Graphical Abstract…”
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Early Detection and Classification of Diabetic Retinopathy: A Deep Learning Approach by Mustafa Youldash, Atta Rahman, Manar Alsayed, Abrar Sebiany, Joury Alzayat, Noor Aljishi, Ghaida Alshammari, Mona Alqahtani

“…Diabetes impacts the human body in various ways, one of the most serious being diabetic retinopathy (DR), which can result in severely reduced vision or even blindness if left untreated. …”
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Evaluating CNN Architectures for the Automated Detection and Grading of Modic Changes in MRI: A Comparative Study by Li‐peng Xing, Gang Liu, Hao‐chen Zhang, Lei Wang, Shan Zhu, Man Du La Hua Bao, Yan‐ni Wang, Chao Chen, Zhi Wang, Xin‐yu Liu, Shuai Zhang, Qiang Yang

“…ABSTRACT Objective Modic changes (MCs) classification system is the most widely used method in magnetic resonance imaging (MRI) for characterizing subchondral vertebral marrow changes. …”
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Severe hyperchloremic metabolic acidosis with SGLT2 inhibitors in patients with urinary diversion by Carolina Gomes, João Barbosa Barroso, Ana Isabel Oliveira, Sofia Guerreiro Cruz, Liliana Cunha, Ana Azevedo

“…Urinary diversion after cystectomy using autologous intestinal segments has been the gold standard treatment in several urinary tract diseases. The most frequent metabolic consequence is hyperchloremic metabolic acidosis, due to ammonium hydrogen and chloride ions absorption in exchange for the excretion of bicarbonate and sodium ions in the bowel conduit.Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a class of antihyperglycemic agents that block the reabsorption of filtered glucose in the renal proximal convoluted tubules, promoting greater urinary glucose and sodium excretion.The authors describe two cases of patients with bowel conduit and mild/severe hyperchloremic metabolic acidosis, after starting SGLT2 inhibitors. …”
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Severe hyperchloremic metabolic acidosis with SGLT2 inhibitors in patients with urinary diversion by Carolina Gomes, João Barbosa Barroso, Ana Isabel Oliveira, Sofia Guerreiro Cruz, Liliana Cunha, Ana Azevedo

“…Urinary diversion after cystectomy using autologous intestinal segments has been the gold standard treatment in several urinary tract diseases. The most frequent metabolic consequence is hyperchloremic metabolic acidosis, due to ammonium hydrogen and chloride ions absorption in exchange for the excretion of bicarbonate and sodium ions in the bowel conduit.Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a class of antihyperglycemic agents that block the reabsorption of filtered glucose in the renal proximal convoluted tubules, promoting greater urinary glucose and sodium excretion.The authors describe two cases of patients with bowel conduit and mild/severe hyperchloremic metabolic acidosis, after starting SGLT2 inhibitors. …”
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PatchOut: A novel patch-free approach based on a transformer-CNN hybrid framework for fine-grained land-cover classification on large-scale airborne hyperspectral images by Renjie Ji, Kun Tan, Xue Wang, Shuwei Tang, Jin Sun, Chao Niu, Chen Pan

“…Airborne hyperspectral systems can provide high-resolution hyperspectral images (HSIs) covering large scenes, enabling fine-grained land-cover classification. However, the most popular patch-based methods are limited by low computational efficiency and broken classification results, which hinders the full utilization of this powerful technology in Earth observation applications. …”
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Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approach by Elizabeth P.V. Le, Mark Y.Z. Wong, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Jonathan R. Weir-McCall, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Fulvio Zaccagna, Chris Wall, Rouchelle Sriranjan, Andrej Corovic, Yuan Huang, Elizabeth A. Warburton, Evis Sala, Michael Roberts, Carola-Bibiane Schönlieb, James H.F. Rudd

“…Explainability revealed consistent patterns in the most important radiomic features. Conclusions: Our study highlights the potential of novel image analysis techniques in extracting quantitative information beyond calcification in the identification of CAD. …”
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Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study by Chi-Ching Tsang, Chenyang Zhao, Yueh Liu, Ken P. K. Lin, James Y. M. Tang, Kar-On Cheng, Franklin W. N. Chow, Weiming Yao, Ka-Fai Chan, Sharon N. L. Poon, Kelly Y. C. Wong, Lianyi Zhou, Oscar T. N. Mak, Jeremy C. Y. Lee, Suhui Zhao, Antonio H. Y. Ngan, Alan K. L. Wu, Kitty S. C. Fung, Tak-Lun Que, Jade L. L. Teng, Dirk Schnieders, Siu-Ming Yiu, Susanna K. P. Lau, Patrick C. Y. Woo

“…While morphological examination is the most widely used for Aspergillus identification in clinical laboratories, PCR–sequencing and MALDI–TOF MS are emerging technologies in more financially-competent laboratories. …”
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Correction of crop water deficit indicators based on time-lag effects for improved farmland water status assessment by Yujin Wang, Zhitao Zhang, Yinwen Chen, Shaoshuai Fan, Haiying Chen, Xuqian Bai, Ning Yang, Zijun Tang, Long Qian, Zhengxuan Mao, Siying Zhang, Junying Chen, Youzhen Xiang

“…However, time-lag effects between canopy temperature (Tc) and environmental factors can influence their correlation with SWC, thereby complicating the identification of the most reliable diagnostic indicator. This study conducted a two-year field experiment on winter wheat under four irrigation levels (80–95 %, 65–80 %, 50–65 %, and 40–50 % field capacity). …”
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Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review by Seng Hansun, Ahmadreza Argha, Ivan Bakhshayeshi, Arya Wicaksana, Hamid Alinejad-Rokny, Greg J Fox, Siaw-Teng Liaw, Branko G Celler, Guy B Marks

“…ResultsRadiographic biomarkers (n=129, 84.9%) and deep learning (DL; n=122, 80.3%) approaches were predominantly used, with convolutional neural networks (CNNs) using Visual Geometry Group (VGG)-16 (n=37, 24.3%), ResNet-50 (n=33, 21.7%), and DenseNet-121 (n=19, 12.5%) architectures being the most common DL approach. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In ophthalmology, convolutional and deep learning have made it possible to quickly and non-invasively interpret the retina. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Notably, the variant that contributed most to the CNN model was NKAIN2, an ADHD-related gene, which is also associated with metabolic processes. …”
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Quantum ensemble learning with a programmable superconducting processor by Jiachen Chen, Yaozu Wu, Zhen Yang, Shibo Xu, Xuan Ye, Daili Li, Ke Wang, Chuanyu Zhang, Feitong Jin, Xuhao Zhu, Yu Gao, Ziqi Tan, Zhengyi Cui, Aosai Zhang, Ning Wang, Yiren Zou, Tingting Li, Fanhao Shen, Jiarun Zhong, Zehang Bao, Zitian Zhu, Zixuan Song, Jinfeng Deng, Hang Dong, Pengfei Zhang, Wei Zhang, Hekang Li, Qiujiang Guo, Zhen Wang, Ying Li, Xiaoting Wang, Chao Song, H. Wang

“…Abstract Quantum machine learning is among the most exciting potential applications of quantum computing. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…In the spatial domain, the Temporal Convolutional Network (TCN) models long-range dependencies by expanding causal convolutions, thereby capturing local and global spatial relationships. …”
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“Locality – Adaptation” Research of Hydropower Resettlement Communities in the Jinsha River Basin: A Case Study of Ludila Hydropower Station by Fang WANG, Zhuoqi LI, Haoyi XU, Jiaqi YAN

“…ObjectiveWithin human – environment systems, river basins constitute the earliest geographical units of human activity and currently represent the most critical zones of strained human – environment interactions. …”
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Wireless Authentication Method Based on Near-Field Feature Fusion Network by QIU Jiefan, ZHOU Kezhong, ZHU Dongfu, ZHANG Jinhong, CHI Kaikai

“…ObjectiveMost existing WiFi-based authentication methods typically extract gait features from channel state information (CSI) obtained from reflected paths, neglecting the significant changes in CSI when users are in the line-of-sight (LOS) path. …”
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HISTOPATHOLOGIC STUDY OF THE HEPATIC AND RENAL LESIONS INDUCED BY EXPERIMENTAL TOXIC DIETARY APPLICATION OF AFLATOXIN B; IN BROILER CHICKS by am Bader Falih, Ena

“…Also there was degeneration in proximal convoluted tubules mostly as hyaline degeneration especially at 0.5 ppm dose level. …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. …”
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Zoon’s Balanitis – Update of Clinical Spectrum and Management by Vineet Relhan, Abhinav Kumar, Aneet Kaur

“…It is a clinical mimicker of other commoner genital dermatoses and is mostly a diagnosis of exclusion when other diseases have been ruled out. …”
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