Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

“…Furthermore, the absence of tailored fracturing designs has caused substantial variations in post-fracturing production performance among adjacent wells. …”
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The Robust Vessel Segmentation and Centerline Extraction: One-Stage Deep Learning Approach by Rostislav Epifanov, Yana Fedotova, Savely Dyachuk, Alexandr Gostev, Andrei Karpenko, Rustam Mullyadzhanov

“…The proposed end-to-end framework directly predicts the centerline as a polyline with real-valued coordinates, thereby eliminating the need for post-processing steps commonly required by previous methods that infer centerlines either implicitly or without ensuring point connectivity. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review by Ikram Bagri, Karim Tahiry, Aziz Hraiba, Achraf Touil, Ahmed Mousrij

“…This research aimed to conduct a comprehensive examination of the current methodologies employed in the stages of vibration signal analysis, which encompass preprocessing, processing, and post-processing phases, ultimately leading to the application of Artificial Intelligence-based diagnostics and prognostics. …”
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Crack-Based Estimation of Seismic Damage Level in Confined Masonry Walls in the Lima Metropolitan Area Using Deep Learning Techniques by Miguel Diaz, Luis Lopez, Michel Amancio, Italo Inocente, Jhianpiere Salinas, Sergio Isuhuaylas, Erika Flores, Edisson Moscoso

“…In contrast, non-contact methods assess damage remotely, allowing for faster, safer, and large-scale evaluations, especially useful in post-disaster scenarios. However, there are currently no standardized non-contact methods for assessing damage levels in confined masonry walls after damaging seismic events in Peru. …”
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ToxDL 2.0: Protein toxicity prediction using a pretrained language model and graph neural networks by Lin Zhu, Yi Fang, Shuting Liu, Hong-Bin Shen, Wesley De Neve, Xiaoyong Pan

“…After constructing a comprehensive toxicity benchmark dataset, we obtained experimental results on both an original non-redundant test set (comprising pre-2022 protein sequences) and an independent non-redundant test set (a holdout set of post-2022 protein sequences), demonstrating that ToxDL 2.0 outperforms existing state-of-the-art methods. …”
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Predicting troponin biomarker elevation from electrocardiograms using a deep neural network by Truls Råmunddal, Erik Andersson, Zacharias Mandalenakis, Kristofer Skoglund, Araz Rawshani, Elmir Omerovic, Jan Borén, Petur Petursson, Aidin Rawshani, Peter Lundgren, Christian Dworeck, Lukas Hilgendorf, Vibha Gupta, Charlotta Ljungman, Gustav Smith

“…On this dataset, a residual convolutional neural network (ResNet) was trained 10 times, each on a unique split of the data. …”
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MentalAId: an improved DenseNet model to assist scalable psychosis assessment by Muxi Li, Farong Liu, Fei Du, Guolin Hong, Qing Hu, Zhi-Liang Ji, Pan You

“…Abstract Background The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. …”
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The Effectiveness of Deep Learning in the Differential Diagnosis of Hemorrhagic Transformation and Contrast Accumulation After Endovascular Thrombectomy in Acute Ischemic Stroke Pa... by Mehmet Beyazal, Merve Solak, Murat Tören, Berkutay Asan, Esat Kaba, Fatma Beyazal Çeliker

“…These labeled images were trained with nine different models under a convolutional neural network (CNN) architecture using a large dataset, such as ImageNet. …”
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Exploiting the power of stepwise intraoperative irrigant activation to maximize oval canal disinfection: an ex-vivo investigation by Mohammed Turky, Shaimaa Hamdy, Soha Elhady

“…At the end of the chemo-mechanical preparation, a bacterial sampling was conducted to determine the number of colony-forming units per mL (CFU//mL), and the outcomes were compared with one-way ANOVA and Games-Howell post hoc test with the significance level set at 5%. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…Using a pre-trained convolutional neural network, the model identified tumor areas and predicted TP53 mutations with a Dice coefficient score of 0.82. …”
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Automating tephra fall building damage assessment using deep learning by E. Tennant, S. F. Jenkins, V. Miller, R. Robertson, B. Wen, S.-H. Yun, B. Taisne

“…This is the first attempt to automate tephra fall building damage assessment solely using post-event data. We expect that incorporating additional training data from future eruptions will further refine our model and improve its applicability worldwide. …”
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Building a machine learning-assisted echocardiography prediction tool for children at risk for cancer therapy-related cardiomyopathy by Lindsay A. Edwards, Christina Yang, Surbhi Sharma, Zih-Hua Chen, Lahari Gorantla, Sanika A. Joshi, Nicolas J. Longhi, Nahom Worku, Jamie S. Yang, Brandy Martinez Di Pietro, Saro Armenian, Aarti Bhat, William Border, Sujatha Buddhe, Nancy Blythe, Kayla Stratton, Kasey J. Leger, Wendy M. Leisenring, Lillian R. Meacham, Paul C. Nathan, Shanti Narasimhan, Ritu Sachdeva, Karim Sadak, Eric J. Chow, Patrick M. Boyle

“…Methods We designed a series of deep convolutional neural networks (DCNNs) for prediction of cardiomyopathy (shortening fraction ≤ 28% or ejection fraction ≤ 50% on two occasions) for at-risk survivors ≥ 1-year post initial cancer therapy. …”
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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

“…This study developed and investigated the performance of convolutional neural network (CNN) in detecting and grading MCs based on their maximum vertical extent. …”
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Co-Infection of <i>Culex tarsalis</i> Mosquitoes with Rift Valley Fever Phlebovirus Strains Results in Efficient Viral Reassortment by Emma K. Harris, Velmurugan Balaraman, Cassidy C. Keating, Chester McDowell, J. Brian Kimble, Alina De La Mota-Peynado, Erin M. Borland, Barbara Graham, William C. Wilson, Juergen A. Richt, Rebekah C. Kading, Natasha N. Gaudreault

“…This can have severe implications in areas where RVFV is endemic and convolutes our ability to anticipate transmission and circulation in novel geographic regions. …”
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Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking by Ziheng Feng, Jiliang Zhao, Liunan Suo, Heguang Sun, Huiling Long, Hao Yang, Xiaoyu Song, Haikuan Feng, Bo Xu, Guijun Yang, Chunjiang Zhao

“…Most phenological monitoring methods are post–seasonal and heavily rely on high–frequency time–series data. …”
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Mild autonomous cortisol secretion leads to reduced volumetric BMD at lumbar spine in patients with primary aldosteronism by Nabeel Mansour, Denise Bruedgam, Daniel Heinrich, Ulrich Dischinger, Nicole Reisch, Friederike Völter, Friederike Völter, Isabel Stüfchen, Elisabeth Nowak, Stephanie Zopp, Victoriya Vasileva, Osman Öcal, Moritz Wildgruber, Max Seidensticker, Jens Ricke, Martin Bidlingmaier, Martin Reincke, Juínia Ribeiro de Oliveira Longo Schweizer

“…Lumbar volumetric bone mineral density (vBMD) was extracted by a novel convolutional neural network (CNN)-based framework (SpineQ software v1.0) applied to routine CT data, incorporated into the diagnostic protocol for PA. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…To enhance the feature representation and reduce background noise interference, the Convolutional Block Attention Module (CBAM) is embedded after the feature maps. …”
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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

“…At the basin scale, the Patch-level Land Use Simulation Model (PLUS) is employed to analyze land use adaptation changes in the basin during two phases: 2005 –2010 (pre-resettlement period) and 2015 –2020 (post-resettlement period). At the settlement scale, the Mask Region-based Convolutional Neural Network (Mask R-CNN) deep learning model is utilized to identify architectural spatial features, categorizing three typical building types: traditional pitched-roof buildings, uniformly planned flat-roof buildings, and color steel plate-modified structures. …”
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NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC by Rui Wang, Guan Wang, Ying Huang, Yu Jiang, Zhigang Li, Chao Yang, Yuan Zhang, Hengrui Liang, Jianxing He, Zhichao Liu, Hongxu Liu, Jia Zhang, Hong Yu, Guangjian Zhang, Hongshen Deng, Zeping Yan, Wenhai Fu, Jianqi Zheng, Runchen Wang, Houlu Xiao, Zhenlin Chen, Xiaomin Ge, Pingwen Yu, Junke Fu, Bohao Liu, Chudong Wang, Yuechun Lin, Linchong Huang, Fei Cui

“…Conventional size-based imaging criteria offer limited reliability, while biopsy confirmation is available only post-surgery.Methods We retrospectively assembled 509 consecutive NSCLC cases from four Chinese thoracic-oncology centers (March 2018 to March 2023) and prospectively enrolled 50 additional patients. …”
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