PATIENTS WITH DECOMPENSATION OF CHRONIC PULMONARY HEART- REMODELING PARAMETERS OF THE RIGHT ATRIUM AND RIGHT VENTRICLE by A. K. Koyirov, S. R. Kenjaev, S. SH. Khaitov, U. SH. Ganiev, N. T. Egamova, M. S. Mirmaksudov

“…Recently, however, focus has shifted toward the right atrium, with increased right atrial (RA) size included in the diagnostic and prognostic algorithms for patients with pulmonary arterial hypertension. …”
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Let’s Go Bananas: Beyond Bounding Box Representations for Fisheye Camera-Based Object Detection in Autonomous Driving by Senthil Yogamani, Ganesh Sistu, Patrick Denny, Jane Courtney

“…Object detection is a mature problem in autonomous driving, with pedestrian detection being one of the first commercially deployed algorithms. It has been extensively studied in the literature. …”
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19 Predicting daily PM2.5 in Mexico City: A hybrid spatiotemporal modeling approach by Mike He, Ellen Ren, Iván Gutiérrez-Avila, Itai Kloog

“…Important predictors of ground-level PM2.5 included wind (both u and v components), 2-meter mean air temperature, elevation, and the normalized difference vegetation index (NDVI). …”
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Improving time upscaling of instantaneous evapotranspiration based on machine learning models by Danni Yang, Shanshan Yang, Jiaojiao Huang, Shuyu Zhang, Sha Zhang, Jiahua Zhang, Yun Bai

“…Results indicated that XGBoost exhibited the best performance, with a root mean square error (RMSE) generally below 13 W [Formula: see text] in estimating [Formula: see text] from [Formula: see text]. …”
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Specific features of pregnancy in patients with type 1 diabetes in the prepubertal period. Results of a 15-year long clinical observation by Lyubov' Leonidovna Bolotskaya, Natalya Vladimirovna Efremova, Yury Ivanovich Suntsov

“…Nine (56,2%) patientsused ultrashort-acting insulin analogs and the remaining 7 (43,7%) recombinant human insulins. The mean insulin dose was 43,7?11 U/din the 1st trimester, 51,8?…”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…Model performance was evaluated using Normalized Mean Squared Error (NMSE) as the evaluation metric. …”
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Complex Therapy for Intraoperative Blood Loss during Pelvic Bone Repair by Z. G. Marutyan, Yu. V Nikiforov, A. B. Kazantsev, A. A. Ter-Grigoryan

“…Objective: to introduce blood saving technologies and to develop algorithms for management of patients with pelvic fractures. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks by Joshua Larsen, Jeffrey Dunne, Robert Austin, Cassondra Newman, Michael Kudenov

“…We were able to demonstrate automated scoring, as compared to expert visual scoring, with a root mean square error of 0.996 visual scores, on individual images (one image per plot), and 0.800 visual scores when three images were captured of each plot. …”
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A Proposed Image Scaling Technique by Using Bezier Curve by Rafal Ali Sameer

“…This paper proposes a digital image resizing (scaling) approach and explaining how the algorithms have been modified to meet accuracy and performance. …”
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Short-Term Prediction of Origin–Destination Passenger Flow in Urban Rail Transit Systems with Multi-Source Data: A Deep Learning Method Fusing High-Dimensional Features by Huanyin Su, Shanglin Mo, Huizi Dai, Jincong Shen

“…In the spatial module, the K-means and K-shape algorithms are used to classify OD pairs from multiple perspectives and capture the spatial features, reducing the difficulty of OD passenger flow predictions with large-scale and complex characteristics. …”
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Significance of Chest Computed Tomography Scan Findings at Time of Diagnosis in Patients with COVID-19 Pneumonia by Rajaa Suhail Najim, Ahmed Diaa Abdulwahab, Dina Nasih Tawfeeq

“…Background and objectives: Many published reports demonstrated the cardinal hallmark of COVID-19 infection, such as bilateral ground glass opacities (GGO) with or without consolidation in posterior and peripheral lungs fields. Various CT algorithms including CT scoring system were used to assess quantitively and qualitatively the severity of COVID-19 pneumonia. …”
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Deep learning and georeferenced RGB-D imaging for hydroponic strawberry yield mapping by Camilo Pardo-Beainy, Carlos Parra, Leonardo Solaque, Won Suk Lee

“…This study evaluates four instance segmentation algorithms: YOLOv8n, YOLOv8s, YOLOv8m, and YOLOv8l, along with a low-cost GNSS RTK system to detect and count strawberries in a hydroponic environment. …”
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Prevention of falls in hospitalized patients—evaluation of the effectiveness of a monitoring system (Verso Vision) developed with artificial intelligence by Corrado Gervasi, Erik Perego, Francesca Galli, Valter Torri, Massimo Castoldi, Emilio Bombardieri

“…The mean age of the 362 patients was 75.3 years and 150 were females (41.4%). …”
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Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning by Max Anjos, Fred Meier

“…Even with limited traffic information, the model effectively generalized to new road segments. For PC, the Relative Mean Difference (RMD) was +16% on average. For HDT, RMD was 19% for traffic flow and 2.6% for average speed. …”
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Modelling and simulation of the block pouring construction system considering spatial–temporal conflict of construction machinery in arch dams by Zhipeng Liang, Jiayao Peng, Chunju Zhao, Huawei Zhou, Dongfeng Li, Yihong Zhou, Quan Liu, Xiaodong Li, Cheng Zhang, Fang Wang

“…Scientific simulation and preview of the pouring construction process and analysis of the level, time, and influence degree of the outbreak of spatial–temporal conflict are significant means to optimize the construction organization and management. …”
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Evolutionary and expression analysis of sugar transporters from Tartary buckwheat revealed the potential function of FtERD23 in drought stress by Dili Lai, Md. Nurul Huda, Yawen Xiao, Tanzim Jahan, Wei Li, Yuqi He, Kaixuan Zhang, Jianping Cheng, Jingjun Ruan, Meiliang Zhou

“…Moreover, gene co-expression analyses using weighted gene co-expression network analysis (WGCNA) and fuzzy c-means algorithm (FCMA) identified six transcription factors that may regulate FtERD23 expression and are involved in plant drought tolerance. …”
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The association between cerebral small vessel disease and unfavorable hematoma morphology in primary intracerebral hemorrhage by Wenqi Jiang, Xinyang Li, Yutao Tan, Wen Guo, Shihong Zhang, Bo Wu, Lu Ma, Ming Liu, Mangmang Xu

“…Futhermore, we employed unsupervised machine learning using K-means algorithm to cluster patients into different groups according to CSVD burden, and the results showed that cluster with higher CSVD burden was less likely to be associated with unfavorable hematoma morphology such as black hole and higher CHMS after correcting for confounders.Conclusions Lower CSVD burden might be associated with higher incidence of unfavorable hematoma morphology features, such as CTBS ≥4 and higher CHMS.…”
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The dynamics of lowland river sections of Danube and Tisza in the Carpathian basin by Imre M. Jánosi, Imre M. Jánosi, István Zsuffa, István Zsuffa, Tibor Bíró, Boglárka O. Lakatos, Boglárka O. Lakatos, András Szöllősi-Nagy, Zsolt Hetesi, Zsolt Hetesi

“…Extracted periods by the Lomb-Scargle algorithm (suitable for unevenly sampled time series) and the long-time means indicate the expected annual seasonality. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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