A novel CFD-MILP-ANN approach for optimizing sensor placement, number, and source localization in large-scale gas dispersion from unknown locations by Yiming Lang, Michelle Xin Yi Ng, Kai Xiang Yu, Binghui Chen, Peng Chee Tan, Khang Wei Tan, Weng Hoong Lam, Parthiban Siwayanan, Kek Seong Kim, Thomas Shean Yaw Choong, Joon Yoon Ten, Zhen Hong Ban

“…The Internet of Things (IoT) enables online real-time gas concentrations, but its capability to predict leak sources accurately remains a challenge. …”
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A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinoma in situ of The Breast by Mary E. Edgerton, Yao-Li Chuang, Paul Macklin, Wei Yang, Elaine L. Bearer, Vittorio Cristini

“…Using the ensuing ratios, we applied the model to determine a predicted surgical volume or tumor size. We then corroborated our hypothesis by comparing the predicted size of each tumor based on our model with the actual size of the pathological specimen after tumor excision (R2 = 0.74—0.88). …”
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Development of the Dutch translational knowledge agenda for inherited metabolic diseases by I. J. Hieltjes, J. H. van derLee, M. C. Groenendijk, G. vanHaaften, P. M. vanHasselt, R. J. Lunsing, G. J. J. vanProoijen, E. M. deRuiter, F. J. vanSpronsen, N. M. Verhoeven‐Duif, A. deVreugd, M. Wagenmakers, H. Zweers, H. Dekker, H. R. Waterham, C. D. vanKarnebeek, R. J. A. Wanders, R. A. Wevers

“…The resulting top 10 research questions cover multiple themes, i.e. prediction of disease progression, development of novel tools, mechanistic insights, improved diagnostics, therapeutic integration of multi‐omics techniques, assessment of impact on daily life, expanding treatment avenues, optimal study designs, effect of lifestyle interventions, and data utilization using FAIR principles. …”
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Deep learning captures the effect of epistasis in multifactorial diseases by Vladislav Perelygin, Alexey Kamelin, Alexey Kamelin, Nikita Syzrantsev, Layal Shaheen, Layal Shaheen, Anna Kim, Nikolay Plotnikov, Anna Ilinskaya, Valery Ilinsky, Alexander Rakitko, Alexander Rakitko, Maria Poptsova

“…BackgroundPolygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. …”
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Evaluating the Performance of Artificial Intelligence-Based Large Language Models in Orthodontics—A Systematic Review and Meta-Analysis by Farraj Albalawi, Sanjeev B. Khanagar, Kiran Iyer, Nora Alhazmi, Afnan Alayyash, Anwar S. Alhazmi, Mohammed Awawdeh, Oinam Gokulchandra Singh

“…The quality of the included studies was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST), and R Studio software (Version 4.4.0) was employed for meta-analysis and heterogeneity assessment. …”
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Mutual associations among responsiveness to differential diagnostic tests for Cushing’s disease, tumor size, and somatostatin receptor 5 expression in corticotroph tumors by Karolina Budzen, Kosuke Mukai, Yuto Mitsui, Michio Otsuki, Atsunori Fukuhara, Satoru Oshino, Youichi Saitoh, Masaharu Kohara, Eiichi Morii, Iichiro Shimomura

“…The areas under the receiver operating characteristic curve for the prediction of high SSTR5 expression via the CRH test, DDAVP test, HDDST, ACTH/cortisol index, and tumor diameter were 0.79, 0.87, 0.80, 0.71, and 0.71, respectively. …”
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Shengxue Busui Decoction activates the PI3K/Akt and VEGF pathways, enhancing vascular function and inhibiting osteocyte apoptosis to combat steroid-induced femoral head necrosis by Manting Liu, Jiexiang Ye, Runtian Wu, Dongqiang Luo, Tao Huang, Dandan Dai, Kexin Wang, Yanping Du, Junwen Ou

“…Cytoscape and machine learning (SVM) were used for target prediction and molecular docking validation. A dexamethasone (Dex)-induced SONFH rat model was established, and SBD was administered for 60 days. …”
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Meteorological Anomalies During Earthquake Preparation: A Case Study for the 1995 Kobe Earthquake (M = 7.3) Based on Statistical and Machine Learning-Based Analyses by Masashi Hayakawa, Shinji Hirooka, Koichiro Michimoto, Stelios M. Potirakis, Yasuhide Hobara

“…Finally, we suggest a joint examination of our two meteorological quantities for their potential use in real short-term EQ prediction, as well as in the future lithosphere–atmosphere–ionosphere coupling (LAIC) studies as the information from the bottom part of LAIC.…”
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Machine Learning-Based Alzheimer’s Disease Stage Diagnosis Utilizing Blood Gene Expression and Clinical Data: A Comparative Investigation by Manash Sarma, Subarna Chatterjee

“…Based on the performance results obtained, and other factors such as early prediction capabilities, this study compares the efficacies of the two types of biomarkers for multistage diagnosis. …”
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Catalytic effect of Fe@Fe2O3 nanowires and Fenton process on carbamazepine removal from aqueous solutions using response surface methodology by M.M. Amin, S. Yousefinejad, M. Dehghani, S. Rahimi

“…The oxidation efficiency (99.5%) achieved under the optimum condition, which was determined by the model, was consistent with the efficiency predicted by the model. The multi-parameter models showed good calibration and prediction abilities with R²₌0.922, R²_adj= 0.907, R²_pred= 0.868. …”
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High Serum Advanced Glycation End Products Are Associated with Decreased Insulin Secretion in Patients with Type 2 Diabetes: A Brief Report by Tsuyoshi Okura, Etsuko Ueta, Risa Nakamura, Yohei Fujioka, Keisuke Sumi, Kazuhisa Matsumoto, Kyoko Shoji, Kazuhiko Matsuzawa, Shoichiro Izawa, Yuri Nomi, Hitomi Mihara, Yuzuru Otsuka, Masahiko Kato, Shin-ichi Taniguchi, Kazuhiro Yamamoto

“…These results suggest that AGE might play a role in the development or prediction of insulin secretory defects in type 2 diabetes.…”
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Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory by Mumtaz Ali, Jesu Vedha Nayahi, Erfan Abdi, Mohammad Ali Ghorbani, Farzan Mohajeri, Aitazaz Ahsan Farooque, Salman Alamery

“…Predicting daily reference evapotranspiration (ETo) plays a significant role in numerous environmental and agricultural applications. …”
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Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients by Xumeng Liu, Huiwen Fang, Dongmei Liang, Qunjuan Lei, Jiaping Wang, Feng Xu, Shaoshan Liang, Dandan Liang, Fan Yang, Heng Li, Jianghua Chen, Yuan Ni, Guotong Xie, Caihong Zeng

“…Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction.Results A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. …”
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Tumor-associated lymphatic vessel density is a postoperative prognostic biomarker of hepatobiliary cancers: a systematic review and meta-analysis by Jin Li, Yu-Bo Liang, Qing-Bo Wang, Yu-Kai Li, Xing-Ming Chen, Wan-Ling Luo, Yawhan Lakang, Zi-Sheng Yang, Yan Wang, Zhi-Wei Li, Yang Ke, Yang Ke, Yang Ke

“…PurposeThis study aimed to investigate whether tumor-associated lymphatic vessel density (LVD) could predict the survival of patients with hepato-biliary-pancreatic (HBP) cancers after radical resection.MethodsA systematic search was conducted using PubMed, Embase, and Cochrane Library from the inception to July 31, 2024 for literature that reported the role of LVD in overall survival (OS) and recurrence-free survival (RFS) of patients with HBP cancers after radical resection.ResultsTen studies with 761 patients were included for the meta-analysis. …”
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Exploration of linear and interpretable models for quantification of cell parameters via contactless short-wave infrared hyperspectral sensing by Anjana Hevaganinge, Eva Lowenstein, Anna Filatova, Mihir Modak, Nandi Thales Mogo, Bryana Rowley, Jenny Yarmowsky, Joshua Ehizibolo, Ravidu Hevaganinge, Amy Musser, Abbey Kim, Anthony Neri, Jessica Conway, Yiding Yuan, Maurizio Cattaneo, Sui Seng Tee, Yang Tao

“…Finally, the model provides sparse interpretable weight matrices that hint at the underlying solution changes that correlate to each cell parameter prediction.…”
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Implementation of Compensation-Sensitive Shot-Style-Feedback of Aiming Point Training Data at the Swiss Shooting Federation by Dino Tartaruga, Ralf Kredel

“…Furthermore, some technical characteristics even have predictive validity for real shooting performance and therefore appear to be suitable for talent identification. …”
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Perbandingan Prediksi Penggunaan Listrik dengan Menggunakan Metode Long Short Term Memory (LSTM) dan Recurrent Neural Network (RNN) by Nurfatima Selle, Novanto Yudistira, Candra Dewi

“…Therefore, we need a system that can predict the use of electricity by leveraging historical data on previous electricity usage. …”
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Multiomics identify the gene expression signature of the spinal cord during aging process by Lintao Xu, Jingyu Wang, Jinjie Zhong, Weiwei Lin, Gerong Shen, Ning He, Xingjia Mao, Chunyan Fu, Zhaobo Huang, Fengdong Zhao, Xin Ye, Yongjian Zhu, Mingzhi Zheng, Hui Li, Lin-lin Wang, Kai Zhong, Lijun Zhu, Ying-ying Chen

“…Pathway enrichment analysis of differentially expressed genes shows that senescence in spinal cords is related to phagosome function, neuroinflammation, ferroptosis, and necroptosis. Prediction of upstream transcription factors and interactome analysis identify Spi1 as a transcription factor that potentially plays a core role in senescent spinal cords. …”
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Apolipoprotein A-V Is a Novel Diagnostic and Prognostic Predictor in Pediatric Patients with Sepsis: A Prospective Pilot Study in PICU by Chunxia Wang, Yun Cui, Huijie Miao, Xi Xiong, Jiaying Dou, Lujing Shao, Xiaomeng Tang, Yucai Zhang

“…Moreover, the findings of the present study suggest a prognostic value of ApoA5 in children with sepsis, and lower serum ApoA5 than 822 ng/mL predicts worse outcome in pediatric sepsis.…”
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Construction of a novel cuproptosis-related gene signature and integrative analyses in cholangiocarcinoma by Liye Wang, Pan Li, Shuai Gong, Lina Pang, Mingyu Li, Chi Zhang, Shengli Zhang, Xiaoke Zhang, Guozhong Jiang, Wei He

“…We then assessed the values of this signature in prognostic prediction, immune infiltration, and therapeutic responses in CCA. …”
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