From theoretical models to practical deployment: A perspective and case study of opportunities and challenges in AI-driven cardiac auscultation research for low-income settings. by Felix Krones, Benjamin Walker

“…The difficulty with which this model, and other state-of-the-art models, generalise to out-of-distribution data is also discussed. …”
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The nexus between healthcare provider distribution and neonatal mortality based on the context of maternal and child healthcare services in Pakistan by Rashed Nawaz, Neelum Khalid, Fatima Ajmal, Mohammad Fazel Akbary, Shaoqing Gong, Zhongliang Zhou

“…Abstract Background Healthcare provider dearth, particularly in Low and Middle-income countries (LMICs), reduces the development towards improved healthcare outcomes and accomplish the Sustainable Development Goals (SDGs-3). …”
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UTransBPNet for cuffless and calibration-free blood pressure estimation under dynamic conditions by Yali Zheng, Hongda Huang, Jiasheng Gao, Jingyuan Hong, Shenghao Wu, Yuanting Zhang, Qing Liu

“…The analysis also highlights the impact of dataset characteristics on model performance, such as distribution shift, distribution imbalance and individual BP variability, highlighting the need for well-curated data to ensure generalizability. …”
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Employing Quantum Entanglement for Real-Time Coordination of Distributed Electric Vehicle Charging Stations: Advancing Grid Efficiency and Stability by Dawei Wang, Hanqi Dai, Yuan Jin, Zhuoqun Li, Shanna Luo, Xuebin Li

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Terrestrial Spatial Distribution and Summer Abundance of Antarctic Fur Seals (Arctocephalus gazella) Near Palmer Station, Antarctica, From Drone Surveys by Gregory D. Larsen, Megan A. Cimino, Julian Dale, Ari S. Friedlaender, Marissa A. Goerke, David W. Johnston

“…Using repeat animal counts and photogrammetric data products, we modeled fur seal abundance at survey sites over the period of observation, modeled habitat suitability based on fine‐scale topographic habitat characteristics, and estimated abundance across terrestrial habitats near Palmer Station as a function of these products. …”
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INVERSE GAUSSIAN REGRESSION MODELING AND ITS APPLICATION IN NEONATAL MORTALITY CASES IN INDONESIA by M. Fathurahman

“…Inverse Gaussian Regression (IGR) is a suitable model for modeling positively skewed response data, which follows the inverse Gaussian distribution. …”
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An Advanced Deep Learning Model for Identifying Blue Horizontal-branch Stars from LAMOST DR10 by Yuhang Zhang, Yude Bu, Jiangchuan Zhang, Ke Wang, Huili Wu, Mengmeng Zhang, Shanshan Li, Jingzhen Sun, Xiaoming Kong, Zhenping Yi, Meng Liu

“…With massive spectral data provided by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), we aim to identify more potential BHB stars using machine learning methods. …”
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Leveraging Vision Foundation Model via PConv-Based Fine-Tuning with Automated Prompter for Defect Segmentation by Yifan Jiang, Jinshui Chen, Jiangang Lu

“…Recently, the emergence of foundation models driven by powerful computational resources and large-scale training data has brought about a paradigm shift in deep learning-based image segmentation. …”
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A cluster-based local modeling paradigm for high spatiotemporal resolution VPD prediction using multi-source data and machine learning by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…Currently, VPD reanalysis data suffers from relatively low resolution and insufficient accuracy validation. …”
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Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study by Mengdie Liu, Wen Guo, Jin Peng, Jinhui Wu

“…Finally, based on the nomogram risk score, patients were stratified into risk groups and survival curves were plotted, illustrating a significantly lower survival probability in the high-risk group compared to the low-risk group (p < 0.0001).ConclusionUtilizing advanced statistical and machine learning techniques, we developed and validated a prognostic model for SP in the older adult that integrates multimodal data, enhancing predictive accuracy and reliability. …”
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Transdermal delivery of antenatal steroids to promote fetal lung maturation: Proof of principle data from sheep and non-human primate models by Sean W. D. Carter, Ayça Altay Benetti, Ryan Tze Liang Sia, Giorgia Pastorin, Erin L. Johnson, Kay Yi Michelle Seah, Haruo Usuda, Hannah R. S. Watson, Yusaku Kumagai, Qin Wei, Xiawen Liu, Roberto Orefice, Marianne Bon, Zubair Amin, Agnihotri Biswas, Tsukasa Takahashi, Noriyoshi Mochii, Yuya Saito, Hideyuki Ikeda, Masatoshi Saito, Mahesh A. Choolani, Sebastián E. Illanes, Matthew W. Kemp

“…To assess the efficacy of transdermal betamethasone on fetal lung maturation, we used a preterm sheep model of pregnancy comparing postnatal ventilation outcomes. …”
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Learning from low precision samples by Ji In Choi, Madeleine Georges, Jung Ah Shin, Olivia Wang, Tiffany Zhu, Tapan Shah

“…A simple, effective method is to learn machine learning models from quantized data stored with low arithmetic precision (1-8 bits). …”
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A New Model for Prediction of Heat Eddy Diffusivity in Pipe Expansion Turbulent Flows

“…Furthermore, an appropriate low Reynolds number k — e model is adopted for calculation of eddy viscosity. …”
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Analysis of periodic wave soliton structure for the wave propagation in nonlinear low–pass electrical transmission lines through analytical technique by Mujahid Iqbal, Jianqiao Liu, Aly R. Seadawy, Huda Daefallh Alrashdi, Reem Algethamie, Abeer Aljohani, Ce Fu

“…The nonlinear LPETLs model having important implications in sciences and engineering such as communication and electronic engineering included system of signal distribution in cable television, connection system of radio receiver and transmitter and its antennas, computer networking connected system, routing call truck lines of telephone switching centers, high speed data buses in computers and many others. …”
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Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems by Hui Wu, Zhijun Jin, Su Jiang, Hewei Tang, Joseph P. Morris, Jinjiang Zhang, Bo Zhang

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Prediction of potential invasion range of alien plant Peperomia pellucida in China by DONG Xu, CHEN Xiuzhi, LOU Yuxia, GUO Shuiliang

“…Among these ecological niche models, maximum entropy (MaxEnt) model has higher accuracy of predicted results with small sample size.According to 12 environmental variables from the global climate environment database (http://www.worldclim.org/) and 649 occurrence records of P. pellucida in the world from the global biodiversity database (http://data.gbif.org/welcome.htm) and the Chinese Virtual Herbarium (http://www.cvh.org.cn/cms/), a prediction of P. pellucida potential distribution was conducted using MaxEnt model and ArcGis 9.3 software. …”
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Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt by Sunarwan Asuhadi, Mukti Zainuddin, Safruddin Safruddin, Musbir Musbir

“…MaxEnt was chosen for its ability to predict potential distribution areas based on presence data and environmental factors. …”
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Isabelline Wheatear (<i>Oenanthe isabellina</i>), a New Species for the Republic of Moldova: A Regional Review of Species Expansion by Mihail Ghilan, Vitalie Ajder, Silvia Ursul, Emanuel Ștefan Baltag

“…This is likely due to several factors, including its recent entry into the country’s territory, potentially from two different directions at different times. The new data and predictive models provide valuable insights into the current distribution and future expansion potential of this species, underscoring the dynamic nature of avian responses to climate change.…”
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Status Quo and Prospect of Multi-source Heterogeneous Data Fusion Technology for New Power System by Zhen WANG, Dong LIU, Chongyou XU, Jiaming WENG, Fei CHEN

“…In the context of energy transition, the new power system is being built continuously with the goal of being clean and low-carbon, open and interactive. With the fast development of monitoring technology and communication technology, the data sources of power system have become more diverse and the structures of the data have become more complex, which provides a data basis for and at same time brings new challenges to the new power system data fusion. …”
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Highly suitable areas for tea (Camellia sinensis) production will decline under future climate change scenarios by Jintu Kumar Bania, Jyotish Ranjan Deka, Arnab Paul, Arun Jyoti Nath, Gudeta Weldesemayat Sileshi, Ashesh Kumar Das

“…We assess the current and future habitat suitability of tea across the globe under two shared socio-economic pathways (SSPs = SSP2.4-5 and SSP5.8-5) for 2050 and 2070 and determine the key factors that influence tea distribution. We employed an ensemble of five species distribution models to assess the tea distribution. …”
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