Organization of physical interactomes as uncovered by network schemas. by Eric Banks, Elena Nabieva, Bernard Chazelle, Mona Singh

“…Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. …”
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Propensity to childhood anxiety and depression due to exposure to adversity: A multidimensional construct. by Angélica C G Santos, Ariane Silva, Matheus Libório, Cristiane Neri Nobre, Hasheem Mannan, Marcos Flávio S V D'Angelo

“…The literature does not present a consensus on the composition of indicators that make predictions, prognostic algorithms, or management strategies in mental health promotion and prevention. …”
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Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Triglyceride-glucose (TyG) index demonstrated predictive ability for a number of diseases. In an effort to enhance clinical care and early warning systems, this study examined the association between the TyG index and sepsis risk with the aim of improving clinical care and early warning systems. …”
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Validation of ICD‐10 Consensus Code Set for Cirrhosis Detection Using Electronic Health Records in an Asian Population by Jason Pik‐Eu Chang, Hong‐Yi Lin, Pooi‐Ling Loi, Jeanette Pei‐Xuan Ng, Marianne De Roza, Rahul Kumar, Hiang‐Keat Tan, Chanda Kendra Ho, Wei‐Quan Teo, Amber Hwa Hwa Chung, Prema Raj

“…We evaluated the consensus code set's sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in identifying cirrhosis cases. …”
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Developing Laterality-Specific Computable Phenotypes from Electronic Health Record Data, Employing Treatment-Warranted Diabetic Macular Edema as a Use Case by Kaili Ding, MBBS, MS, Tracy Z. Lang, BS, Roberta McKean-Cowdin, PhD, Hossein Ameri, MD, PhD, Narsing A. Rao, MD, Brian C. Toy, MD

“…Purpose: To develop a general algorithm employing structured and unstructured electronic health record (EHR) data to identify laterality-specific treatment-warranted disease more accurately at the longitudinal eye level. …”
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Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol by Martin Eklund, Brett Delahunt, Lars Egevad, Hemamali Samaratunga, Mattias Rantalainen, Marcello Gambacorta, Einar Gudlaugsson, Bodil Ginnerup Pedersen, Xiaoyi Ji, Karina Dalsgaard Sørensen, Kelvin Szolnoky, Nita Mulliqi, Anders Blilie, Henrik Olsson, Matteo Titus, Geraldine Martinez Gonzalez, Sol Erika Boman, Masi Valkonen, Svein Reidar Kjosavik, José Asenjo, Paolo Libretti, Marcin Braun, Radzislaw Kordek, Roman Łowicki, Kristina Hotakainen, Päivi Väre, Benedicte Parm Ulhøi, Pekka Ruusuvuori, Toyonori Tsuzuki, Emilius Adrianus Maria Janssen, Kimmo Kartasalo

“…Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images show promise in improving the accuracy and efficiency of histopathological assessments. …”
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Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images by Ke Zhang, Youhui Qiu, Songwei Feng, Han Yin, Qi Liu, Yuxin Zhu, Haoyu Cui, Xiaoying Wei, Guoqing Wang, Xiangxue Wang, Yang Shen

“…Conclusions The models we constructed enables accurate discrimination between tumor and non-tumor tissues in ovarian cancer as well as the prediction of HRD status for patients with ovarian cancer.…”
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Accurate Solar Radiation Forecasting Through Feature-Enhanced Decision Trees and Wavelet Decomposition by Gaizen Soufiane, Abbou Ahmed, Fadi Ouafia

“…This study explores the efficacy of the decision tree algorithm in predicting solar power generation, addressing the inherent variability in photovoltaic (PV) energy production due to weather conditions. …”
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Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…The STL, the turbulent self-noise reduction or a weighting function of the STL and turbulent self-noise reduction of FGM acoustic windows is chosen as the optimization objective. …”
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Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory by Efi Safikou, Krishna R. Pattipati, George M. Bollas

“…We propose a fault diagnosis approach that integrates symbolic regression and information theory to optimize inferential sensors, which, along with traditional detection techniques and hard sensors, contribute to a comprehensive fault detection and diagnosis algorithm. Additionally, we introduce an advanced predictive scheme to estimate time-dependent fault evolution functions that enable us to compute the remaining useful life (RUL) of the system. …”
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Frequency-constrained optimal power-gas flow with fast frequency response from power-to-gas units by Yu Liang, Xia Zhao

“…The substantial increase in renewable energy integration has resulted in a reduction in inertia and frequency regulation resources within the power system. …”
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A public benchmark for human performance in the detection of focal cortical dysplasia by Lennart Walger, Matthias H. Schmitz, Tobias Bauer, David Kügler, Fabiane Schuch, Christophe Arendt, Tobias Baumgartner, Johannes Birkenheier, Valeri Borger, Christoph Endler, Franziska Grau, Christian Immanuel, Markus Kölle, Patrick Kupczyk, Asadeh Lakghomi, Sarah Mackert, Elisabeth Neuhaus, Julia Nordsiek, Anna‐Maria Odenthal, Karmele Olaciregui Dague, Laura Ostermann, Jan Pukropski, Attila Racz, Klaus von derRopp, Frederic Carsten Schmeel, Felix Schrader, Aileen Sitter, Alexander Unruh‐Pinheiro, Marilia Voigt, Martin Vychopen, Philip vonWedel, Randi vonWrede, Ulrike Attenberger, Hartmut Vatter, Alexandra Philipsen, Albert Becker, Martin Reuter, Elke Hattingen, Alexander Radbruch, Rainer Surges, Theodor Rüber

“…Performance was measured based on the overlap between predicted regions of interest (ROIs) and ground‐truth lesion masks, using the Dice‐Soerensen coefficient (DSC). …”
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A Study of the Soil–Wall–Indoor Air Thermal Environment in a Solar Greenhouse by Zhi Zhang, Yu Li, Liqiang Wang, Weiwei Cheng, Zhonghua Liu

“…The CFD model and LSTM prediction model have been shown to be superior, and the findings of this study offer a theoretical basis for the optimization of thermal environment control in solar greenhouses.…”
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A Voronoi-Based Location Privacy-Preserving Method for Continuous Query in LBS by Chunguang Ma, Changli Zhou, Songtao Yang

“…Firstly, based on the prediction of a user's moving direction, a cooperative k -anonymity method is proposed without constructing cloaking regions which may lead to efficiency decline in continuous query. …”
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Extracting Pole Characteristics of Complex Radar Targets for the Aircraft in Resonance Region Using RMSPSO_ARMA by Sang Zhou, Huotao Gao, Fangyu Ren

“…The extraction algorithm of target characteristics resonance set at the high-frequency band plays a significant role in defense applications like early warning. …”
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Personalized Product Recommendation Model of Automatic Question Answering Robot Based on Deep Learning by Jie Peng, Jianhui Xu

“…Then, the bidirectional gated recurrent unit (Bi-GRU) is used to construct the score prediction matrix, and through the dynamic collaborative filtering algorithm to integrate the time characteristics of the user’s interest changes. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…Firstly, voxel-based gray-level discretization (binWidth = 25) and Z-Score normalization were applied to preprocess the patient's ROI and normalize the extracted features. Then, the most predictive radiomic features were selected and their corresponding coefficients were evaluated using the correlation coefficient algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. …”
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Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…By employing the Dijkstra algorithm, route optimization resulted in a significant reduction in average route length, from 12.94 ± 3.5 km to 9.42 ± 2.67 km, representing a 9-42% improvement. …”
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Strategies to Reduce Left Anterior Descending Artery and Left Ventricle Organ Doses in Radiotherapy Planning for Left-Sided Breast Cancer by Umut Diremsizoglu, Nezihan Topal, Aykut Oguz Konuk, Ibrahim Halil Suyusal, Dogacan Genc, Onur Ari, Hasan Furkan Cevik, Aysegul Ucuncu Kefeli, Maksut Gorkem Aksu, Emine Binnaz Sarper

“…Conclusions: We achieved significant reductions in all heart, LAD, and LV parameters without making any changes to the planned treatment volume coverage by adding LAD and LV OARs to the optimization algorithms. …”
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Komparasi Machine Learning Berbasis Pso Untuk Prediksi Tingkat Keberhasilan Belajar Berbasis E-Learning by Elin Panca Saputra, Siti Nurajizah, Mawadatul Maulidah, Nadiyah Hidayati, Taufik Rahman

“…While the attributes that have an influence to determine the algorithm on the level of accuracy are Practice Questions, Quizzes, Mid-Semester Exams, and Final Exams. it is evident from our previous studies that the PSO-based neural network algorithm does have a very good advantage. based on ANN is a method that has calculations that build several units of interconnected connectivity, the ANN method with predictive accuracy can be an efficient and good tool for forecasting and classification research in the field of education. …”
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