Characterization of G2/M checkpoint classifier for personalized treatment in uterine corpus endometrial carcinoma by Yiming Liu, Yusi Wang, Shu Tan, Xiaochen Shi, Jinglin Wen, Dejia Chen, Yue Zhao, Wenjing Pan, Zhaoyang Jia, Chunru Lu, Ge Lou

“…Ultimately, an artificial neural network (ANN) and machine learning were employed to develop the G2MC subtypes classifier. …”
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In-vivo high-resolution χ-separation at 7T by Jiye Kim, Minjun Kim, Sooyeon Ji, Kyeongseon Min, Hwihun Jeong, Hyeong-Geol Shin, Chungseok Oh, Robert J. Fox, Ken E. Sakaie, Mark J. Lowe, Se-Hong Oh, Sina Straub, Seong-Gi Kim, Jongho Lee

“…To address these challenges, we developed a novel deep neural network, R2PRIMEnet7T, designed to convert a 7T R2* map into a 3T R2′ map. …”
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Prediction of the cutting tool wear during dry hard turning of AISI D2 steel by using models based on Learning process and GA polyfit by Khaled Djellouli, Kamel Haddouche, Mostefa Belarbi, Zoubir Aich

“…For this purpose, the current research focuses on the development of predictive models of flank wear based on Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Polynomial Fit using Genetic Algorithm (GAPOLYFITN). …”
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Dilated cardiomyopathy signature metabolic marker screening: Machine learning and multi-omics analysis by Xiao-Lei Li, Aibibanmu Aizezi, Yan-Peng Li, Yan-Hong Li, Fen Liu, Qian Zhao, Xiang Ma, Dilare Adi, Yi-Tong Ma

“…The machine learning models based on the seven metabolites all had good accuracy in distinguishing DCM [All area under the curve (AUC) > 0.900], and the artificial neural network (ANN) model performed the most consistently (AUC: 0.919 ± 0.075). …”
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Implemantasi Mask R-CNN pada Perhitungan Tinggi dan Lebar Karang untuk Memantau Pertumbuhan Transplantasi Karang by Naufal Alkhalis, Husaini Husaini, Haekal Azief Haridhi, Cut Nadilla Maretna, Nur Fadli, Yudi Haditiar, Muhammad Nanda, Maria Ulfah, Kris Handoko, Intan Malayana, Arsa Cindy Safitri

“…Penelitian ini mengimplementasikan algoritma Mask Region-based Convolutional Neural Network (Mask R-CNN) dengan Pustaka Detectron2 dalam deteksi dan segmentasi objek untuk menghitung tinggi dan lebar karang transplantasi melalui citra. …”
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Enhancing Precipitation Nowcasting Through Dual-Attention RNN: Integrating Satellite Infrared and Radar VIL Data by Hao Wang, Rong Yang, Jianxin He, Qiangyu Zeng, Taisong Xiong, Zhihao Liu, Hongfei Jin

“…To address this limitation, we introduce the Dual-Attention Recurrent Neural Network (DA-RNN), a model that combines satellite infrared (IR) data with radar-derived vertically integrated liquid (VIL) content. …”
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AI-powered estimation of tree covered area and number of trees over the Mediterranean island of Cyprus by Anna Zenonos, Sizhuo Li, Martin Brandt, Jean Sciare, Philippe Ciais

“…This study presents a deep learning neural network model applied to high resolution (10 cm) airborne images collected during the year 2019, to generate segmented tree crowns and the number of individual trees over selected areas of Cyprus, including a large national forest park, a forest park in the capital city, and a small urban area, encompassing a total studied area of 107km2. …”
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Hybrid dung beetle optimization based dimensionality reduction with deep learning based cybersecurity solution on IoT environment by Amal K. Alkhalifa, Nuha Alruwais, Wahida Mansouri, Munya A. Arasi, Mohammed Alliheedi, Fouad Shoie Alallah, Alaa O. Khadidos, Abdulrhman Alshareef

“…Besides, intrusions are detected using the attention bidirectional recurrent neural network (ABiRNN) model. Finally, an artificial rabbits optimization (ARO) based hyperparameter tuning process is performed, enhancing the overall classification performance. …”
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Automated differentiation of wide QRS complex tachycardia using QRS complex polarity by Adam M. May, Bhavesh B. Katbamna, Preet A. Shaikh, Sarah LoCoco, Elena Deych, Ruiwen Zhou, Lei Liu, Krasimira M. Mikhova, Rugheed Ghadban, Phillip S. Cuculich, Daniel H. Cooper, Thomas M. Maddox, Peter A. Noseworthy, Anthony Kashou

“…Methods In a three-part study, we derive and validate machine learning (ML) models—logistic regression (LR), artificial neural network (ANN), Random Forests (RF), support vector machine (SVM), and ensemble learning (EL)—using engineered (WCT-PC and QRS-PS) and previously established WCT differentiation features. …”
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Data mining and safety analysis of voriconazole in patients with a hematological malignant tumor based on the FAERS database: differences between children and adults by Hao Li, Hao Li, Manxue Jiang, Manxue Jiang, Xiaona Pan, Lingti Kong, Lingti Kong, Lingti Kong

“…Data mining was done using reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS).ResultsA total of 605 ADEs were included: 116 (19.17%) in children and 489 (80.83%) in adults. …”
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Ultra robust negative differential resistance memristor for hardware neuron circuit implementation by Yifei Pei, Biao Yang, Xumeng Zhang, Hui He, Yong Sun, Jianhui Zhao, Pei Chen, Zhanfeng Wang, Niefeng Sun, Shixiong Liang, Guodong Gu, Qi Liu, Shushen Li, Xiaobing Yan

“…Meanwhile, based on the high temperature stability of the device, a voltage-temperature fused multimodal impulse neural network was constructed to achieve 91.74% accuracy in classifying digital images with different temperature labels. …”
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A machine learning model using the snapshot ensemble approach for soil respiration prediction in an experimental Oak Forest by S.N. Ferdous, J.P. Ahire, R. Bergman, L. Xin, E. Blanc-Betes, Z. Zhang, J. Wang

“…We then used the Artificial Neural Network (ANN) regression model to correct the forecasting model errors and perform the final prediction using the snapshot ensemble approach. …”
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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT by Emanuele Trucco, Joanna M Wardlaw, Wenwen Li, Grant Mair, Amos Storkey, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt, Paul Armitage

“…We aimed to develop a deep learning (DL) method using CT brain scans that were labelled but not annotated for the presence of ischaemic lesions.Methods We designed a convolutional neural network-based DL algorithm to detect ischaemic lesions on CT. …”
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Combining machine learning algorithms for bridging gaps in GRACE and GRACE Follow-On missions using ERA5-Land reanalysis by Jaydeo K. Dharpure, Ian M. Howat, Saurabh Kaushik, Bryan G. Mark

“…Unlike previous studies, we use a combination of Machine Learning (ML) methods—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGB), Deep Neural Network (DNN), and Stacked Long-Short Term Memory (SLSTM)—to identify and efficiently bridge the gap between GRACE and GFO by using the best-performing ML model to estimate TWSA at each grid cell. …”
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Self-beneficial transactional social dynamics for cooperation in Shwachman-Diamond syndrome: a mixed-subject analysis using computational pragmatics by Arthur Trognon, Arthur Trognon, Arthur Trognon, Natacha Stortini, Natacha Stortini, Coralie Duman, Coralie Duman, Nami Koïdé, Ewa Skupinska, Ewa Skupinska, Hamza Altakroury, Alizée Poli, Alizée Poli, Loann Mahdar-Recorbet, Loann Mahdar-Recorbet, Blandine Beaupain, Jean Donadieu, Michel Musiol, Michel Musiol, Michel Musiol

“…Dialogues were analyzed using the Topological and Kinetic (2TK) model and a Recurrent Neural Network (RNN), enabling fine-grained computational insights into their interaction patterns.ResultsChildren with SDS exhibited cooperative behaviors shaped by perceived economic benefits, often at the expense of established social norms. …”
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Multi-Temporal Image Fusion-Based Shallow-Water Bathymetry Inversion Method Using Active and Passive Satellite Remote Sensing Data by Jie Li, Zhipeng Dong, Lubin Chen, Qiuhua Tang, Jiaoyu Hao, Yujie Zhang

“…A backpropagation (BP) neural network model is then used to incorporate the initial multispectral information of Sentinel-2 data at each bathymetric point and its surrounding area during the training process. …”
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Enhancing feature selection for multi-pose facial expression recognition using a hybrid of quantum inspired firefly algorithm and artificial bee colony algorithm by Mu Panliang, Sanjay Madaan, Siddiq Ahmed Babikir Ali, Gowrishankar J., Ali Khatibi, Anas Ratib Alsoud, Vikas Mittal, Lalit Kumar, A. Johnson Santhosh

“…The evaluated features are utilized for classifying face expressions by utilizing the deep neural network model, ResNet-50. The presented FER system has been tested using multi-pose facial expression benchmark datasets, including RaF (Radboud Faces) and KDEF (Karolinska Directed Emotional Faces). …”
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Design of an Improved Method for Visual Rendering in the Metaverse Using CIEM and MSRANet by Janapati Venkata Krishna, Priyanka Singh, Regonda Nagaraju, Setti Vidya Sagar Appaji, Attuluri Uday Kiran, K. Spandana

“…Finally, BEER, standing for Bioinspired Energy-Efficient Rendering, borrows from the energy-efficient way of visual processing in the human brain through a spiking neural network that reduces energy consumption by 35% without image quality degradation. …”
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Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…A machine learning (ML) model for predicting nitrate leaching was then developed, with the random forest (RF) model outperforming the support vector machine (SVM), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, achieving an R² of 0.75. …”
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Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland by Wuhua Wang, Jiakui Tang, Na Zhang, Xuefeng Xu, Anan Zhang, Yanjiao Wang, Kaihui Li, Yidan Wang

“…This study utilized machine learning models such as Random Forest (RF), AdaBoost, BP-Neural Network (BPNN), and Stacking Ensemble, combining them with topographic and meteorological data, MODIS reflectance data, and grassland height measurement data. …”
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