Application of deep learning and feature selection technique on external root resorption identification on CBCT images by Nor Hidayah Reduwan, Azwatee Abdul Aziz, Roziana Mohd Razi, Erma Rahayu Mohd Faizal Abdullah, Seyed Matin Mazloom Nezhad, Meghna Gohain, Norliza Ibrahim

“…Kruskal Wallis test revealed a significant difference (p = 0.008) in the prediction accuracy among the eight DLMs. Conclusion In general, all DLMs have similar performance on ERR identification. …”
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High-resolution mapping of peatland CO2 fluxes using drone multispectral images by R. Walcker, C. Le Lay, L. Gandois, A. Elger, V.E.J. Jassey

“…Our predictions were in the range of those found in the satellite remote sensing literature with errors lesser than 0.5 gCO2.m−2.h−1. …”
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Social Acceptance of Smart Glasses in Health Care: Model Evaluation Study of Anticipated Adoption and Social Interaction by Niek Zuidhof, Oscar Peters, Peter-Paul Verbeek, Somaya Ben Allouch

“…In summary, constructs that focus on social interaction could contribute to better explanation and prediction of the expected adoption of smart glasses in health care. …”
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Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTMResearch in context by Xueting Jin, Fangwu Wei, Srinivasa Srivatsav Kandala, Tejas Umesh, Kayleigh Steele, John N. Galgiani, Manfred D. Laubichler

“…By predicting the CM prevalence, our results can inform researchers, epidemiologists, clinicians, and the public in order to assist public health. …”
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Salinity affects the lipid metabolism and intestinal microbial composition of swimming crab Portunus trituberculatus by Meimei Liu, Tong Li, Hao Zhang, Zi Wang, Xugan Wu, Jie He, Zhiguo Dong

“…Bacterial functional pathway prediction has also shown that the KEGG pathways involved in ovarian steroidogenesis, NF-kappa B signaling pathway and regulation of lipolysis in adipocytes increased in 28 ‰ group compared with 19 ‰ group. …”
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A comparative analysis of sphenoid and frontal sinuses using cone beam computed tomography for sex determination by Junaid Ahmed, Namrata, Nanditha Sujir, Nandita Shenoy, Srikant Natarajan, Archana Muralidharan, Ashwin C. Shetty

“…There was an improvement in the accuracy of sex prediction when the linear measurements of FS and SS were considered in combination rather than in isolation. …”
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Glymphatic system clearance and Alzheimer’s disease risk: a CSF proteome-wide study by Natalia Cullell, Giovanni Caruana, Andrea Elias-Mas, Ariane Delgado-Sanchez, Cristina Artero, Maria Teresa Buongiorno, Marta Almería, Nicola J. Ray, Sonia A. L. Correa, Jerzy Krupinski

“…In Stage 2, we validated these proteomic results in a new cohort of aMCI participants (with and without evidence of AD pathology in CSF (aMCI(-) and aMCI/AD( +); n = 22 and 7, respectively) and healthy controls (n = 10). Proteomic prediction models were generated in each ROI. These were compared with demographic-only models for identifying participants with aMCI(-) and aMCI/AD( +) vs controls. …”
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Associations of the Need for Surgery in Emergency Department Patients with Small Bowel Obstructions by Daniel J. Berman, Alexander W. Mahler, Ryan C. Burke, Andrew E. Bennett, Nathan I. Shapiro, Leslie A. Bilello

“…These associations are a step toward building better prediction models and improving decision-making in the ED, allowing for a more adequate treatment plan.…”
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Risk Factors Influencing Cognitive Function in Elderly Patients With Late‐Life Depression: A Scoping Review by Ping Jiang, Yunfeng Gao, Lin Wang, Xiaojun Shao, Lei Zhang, Gang Zhu, Li Duan

“…However, there remains an incomplete understanding of the relevant influencing factors for cognitive impairment in elderly depressed patients, which seriously impedes the development of risk prediction models and the subsequent research on precision intervention programs. …”
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Seasonal dynamics of dissolved organic matter in a small tropical estuary-coastal bay continuum: distribution, transformation, flux, and global perspectives by Pengfei Liu, Kuan Jiang, Qi Tan, Fajin Chen, Renming Jia, Chao Wang, Chao Wang, Chao Wang, Chao Wang

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The ANFIS-RSM based multi-objective optimization and modelling of ultrasound-assisted extraction of polyphenols from jamun fruit (Syzygium cumini) by Mohammad Ganje, Somayyeh Gharibi, Fatemeh Nejatpour, Maryam Deilamipour, Kimia Goshadehrou, Sahra Saberyan, Gholamreza Abdi

“…Error indices demonstrated that ANFIS (R2 = 0.8490–0.9989) outperformed RSM (R2 = 0.9265) in predictive capability, underscoring the relative superiority of ANFIS.…”
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Spectral and coupling characteristics of somatosensory cortex and centromedian thalamus differentiate between pre- and inter-ictal 5–9 Hz oscillations in a genetic rat model of abs... by Eleni Nikalexi, Vladimir Maksimenko, Thomas Seidenbecher, Thomas Budde, Hans-Christian Pape, Annika Lüttjohann

“…In general, pre-ictal oscillations display a unique electrophysiological profile in GAERS that might pave the way for qualification as biomarker for SWD generation and seizure prediction.…”
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Numerical Study of the Effect of Out-of-Plane Distance in the Lateral Direction at the Mid-Span of a Steel Beam on the Sectional Moment Capacity by Ahmed Mohamed Sayed, Nageh M. Ali, Mishal H. Aljarbou, Abdullah Alzlfawi, Salman Aldhobaib, Hani Alanazi, Abdulmalik H. Altuwayjiri

“…For all the beams with out-of-plane distances, all the design codes were unable to predict this ultimate capacity.…”
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Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma by Yan-Hua Zheng, Hong-Yuan Shen, Xiang Chen, Juan Feng, Guang-Xun Gao

“…The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations. …”
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Pharmacological Mechanism of Zuojin Pill for Gastroesophageal Reflux Disease: A Network Pharmacology Study by Mi Lv, Jinke Huang, Jiayan Hu, Wenxi Yu, Ping Liu, Kunli Zhang, Fengyun Wang

“…Subsequently, the obtained data were subjected to further network pharmacological analysis to explore the potential key active compounds, core target genes, and biological processes (BPs) associated with the effect of ZJP against GERD. Finally, the prediction results of NP were validated by MD, and MDS of the optimal core protein-ligand for each component obtained by MD were performed using Gromacs 2020 software. …”
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Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning by Wenting Liang, Weili Duan, Yaning Chen, Gonghuan Fang, Shan Zou, Zhi Li, Zewei Qiu, Haodong Lyu

“…These findings provide critical insights for enhancing flood prediction and optimizing water resource management.…”
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Advanced Machine Learning Ensembles for Improved Precipitation Forecasting: The Modified Stacking Ensemble Strategy in China by Tiantian Tang, Yifan Wu, Yujie Li, Lexi Xu, Xinyi Shi, Haitao Zhao, Guan Gui

“…The MSSS for MSES was above 0.5 in more than half of the evaluations, and the Pg score was consistently above 80, indicating high accuracy in precipitation magnitude prediction. These findings highlight the promise of advanced machine learning strategies like MSES in improving the accuracy and robustness of precipitation forecasts, addressing critical needs in water resource management and disaster mitigation in China.…”
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Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial by Chuan-Ching Tsai, Jin Yong Kim, Qiyuan Chen, Brigid Rowell, X Jessie Yang, Raed Kontar, Megan Whitaker, Corey Lester

“…Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. …”
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The focal mechanism and field investigations of mining-induced earthquake by super-thick and weak cementation overburden strata fracturing by Xianxi Bai, Anye Cao, Changbin Wang, Yaoqi Liu, Chengchun Xue, Xu Yang, Yao Yang, Songwei Wang, Qi Hao

“…The research results provide a reference for the prediction, risk assessment and disaster control of MIEs under extremely thick overburden strata.…”
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Developing transcriptomic biomarkers for TAVO412 utilizing next generation sequencing analyses of preclinical tumor models by Ying Jin, Peng Chen, Huajun Zhou, Guangmao Mu, Simin Wu, Zhengxia Zha, Bin Ma, Chao Han, Mark L. Chiu, Mark L. Chiu

“…Together with specific driver mutation that associated with efficacy and the targets of TAVO412, a set of 21-gene biomarker was identified to predict the efficacy. A biomarker predictor was formulated based on the Linear Prediction Score (LPS) to estimate the probability of patients or tumor model response to TAVO412 treatment. …”
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