Clinical evaluation of Rega 8: an updated genotypic interpretation system that significantly predicts HIV-therapy response. by Jurgen Vercauteren, Gertjan Beheydt, Mattia Prosperi, Pieter Libin, Stijn Imbrechts, Ricardo Camacho, Bonaventura Clotet, Andrea De Luca, Zehava Grossman, Rolf Kaiser, Anders Sönnerborg, Carlo Torti, Eric Van Wijngaerden, Jean-Claude Schmit, Maurizio Zazzi, Anna-Maria Geretti, Anne-Mieke Vandamme, Kristel Van Laethem

“…Success was defined as a viral load below 50 copies/ml or alternatively, a 2 log decrease from the baseline viral load at 8 weeks. The predictive ability of Rega version 8 was analysed in comparison with that of previous evaluated version Rega 5 and two other algorithms (ANRS v2011.05 and Stanford HIVdb v6.0.11). …”
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CD34 evaluation of microvasculature in lung adenocarcinoma and its microvascular density predicts postoperative tumor recurrence by Zijian Qiu, Jiaji Wu, Guanchao Pang, Xia Xu, Jun Lin, Pingli Wang

“…BackgroundAngiogenesis is closely associated with tumor growth and metastasis, and microvascular density (MVD) is currently the clinical standard for evaluating tumor angiogenesis. Thus, the detection of intratumoral MVD is of great significance for understanding disease progression and predicting patient prognosis.MethodsTumor tissue sections of 238 patients with lung adenocarcinoma (LUAD) who underwent radical surgery were retrospectively analyzed. …”
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Evaluation of the Canadian Clinical Practice Guidelines Risk Prediction Tool for Acute Aortic Syndrome: The RIPP Score by Robert Ohle, Sarah McIsaac, Madison Van Drusen, Aaron Regis, Owen Montpellier, Mackenzie Ludgate, Oluwadamilola Bodunde, David W. Savage, Krishan Yadav

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Machine Learning-Based Prediction Model for Multidrug-Resistant Organisms Infections: Performance Evaluation and Interpretability Analysis by Zhao W, Sun P, Li W, Shang L

“…This study evaluated an interpretable machine learning model incorporating SHapley Additive exPlanations (SHAP) to predict MDRO infections in ICU patients.Methods: A retrospective cohort study was conducted on 888 ICU patients (2020– 2022) from a tertiary hospital in China. …”
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Evaluation of hypotension prediction index software in patients undergoing orthotopic liver transplantation: retrospective observational study by Jacek B. Cywinski, Yufei Li, Lusine Israelyan, Roshni Sreedharan, Silvia Perez-Protto, Kamal Maheshwari

“…Methods: This was a retrospective observational study conducted in a tertiary academic center with a large liver transplant program. …”
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Dynamics-based predictions of infinite-dimensional complex systems using dynamical system deep learning method by Hao Li, Jianping Li, Zixiang Wu, Mingyu Wang, Guangcan Liu, Ruipeng Sun, Ruize Li, Ning Wang, Houbin Song, Shixin Zhen

“…The findings demonstrate that the DSDL method exhibits outstanding prediction performance for PDEs. …”
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Tenderness prediction for beef using novel data analysis methods based on system dynamic and acoustic signals by Janna Tholen, Jan Gohe, Helene Dörksen, Theo Kiesel, Matthias Upmann

“…Basically, it is possible to predict the tenderness of roastbeef by taking measurements at the beginning of the maturing process for the end of the maturing period using vibroacoustic methods: Data analysis led to a trend function that roughly reflects the actual tenderness, which is generally higher than the real tenderness represented by the shear-force measurement. …”
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Filter for Traffic Congestion Prediction: Leveraging Traffic Control Signal Actions for Dynamic State Estimation by Younus Hasan Taher, Jit Singh Mandeep, Mohammad Tariqul Islam, Omer Tareq Abdulhae, Ahmed Thair Shakir, Md. Shabiul Islam, Mohamed S. Soliman

“…This study contributes to this domain by enhancing traffic prediction models. Traditional traffic models often fall short in accurately predicting traffic flow, particularly in dynamic urban settings. …”
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Short-term multi-step wind speed prediction using statistical methods and artificial neural networks by İsmail Kırbaş

“…While the wind speedestimation studies in the literature generally focus only on single stepprediction success, detailed evaluation of commonly used estimation methods atthe prospective 12 step level has been carried out.…”
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A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging by Jian Zhang, Jiajin Wang, Hongbo Li, Qin Zhang, Xiangning He, Cui Meng, Xiaoyan Huang, Youtong Fang, Jianwei Wu

“…Data-driven methods, such as artificial intelligence or curve-fitting techniques, offer precise predictions of complex nonlinear relationships. …”
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Machine Learning Methods as a Tool for Analysis and Prediction of Impact Resistance of Rubber–Textile Conveyor Belts by Miriam Andrejiova, Anna Grincova, Daniela Marasova, Zuzana Kimakova

“…The article focuses on the use of machine learning methods as one of the approaches to the analysis and prediction of the impact resistance of rubber–textile conveyor belts. …”
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An Operational Carbon Emission Prediction Model Based on Machine Learning Methods for Urban Residential Buildings in Guangzhou by Lintao Zheng, Kang Luo, Lihua Zhao

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Predicting Gender from Twitter Text Messages Using Methods Based on Artificial Intelligence and Text Analysis by Md. Nyem Hasan Bhuiyan, Anisur Rahman

“…Finally, by conducting a case study based on a dataset of textual Twitter data, the accuracy of different models was investigated based on different evaluation indices. The results showed that models based on NNs, which were vectorized by word2index and word embedding methods, are more accurate in gender classification than models based on ML. …”
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Predicting Three-Dimensional (3D) Printing Product Quality with Machine Learning-Based Regression Methods by Ahmet Burak Tatar

“…Among these methods, GPR demonstrated the highest prediction accuracy for elongation, tensile strength, and roughness, with respective values of 0.98, 0.9, and 1. …”
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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study by Emanuele Frassini, Teddy S. Vijfvinkel, Rick M. Butler, Maarten van der Elst, Benno H. W. Hendriks, John J. van den Dobbelsteen

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Kalman filtering assimilated machine learning methods significantly improve the prediction performance of water quality parameters by Zhenyu Gao, Guoqiang Wang, Jinyue Chen, Lei Fang, Shilong Ren, A. Yinglan, Shuping Ji, Ruobing Liu, Qiao Wang

“…Accurate water quality prediction is essential for effective water pollution prevention and emergency responses. …”
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Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review by Wilson W S Tam, Kang Sim, Jing Ling Tay, Yun Ling Ang

“…Objectives We aimed to examine the predictive accuracy of functioning, relapse or remission among patients with psychotic disorders, using machine learning methods. …”
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Evaluation of Flavor Type of Tobacco Blending Module: A Prediction Model Based on Near-Infrared Spectrum by Lin Wang, Yuhan Guan, Yaohua Zhang

“…Therefore, the proposed method of predicting flavor types based on near-infrared spectral features plays a valuable role in facilitating rapid positioning, scientific evaluation, and cigarette formulation design for tobacco blending modules, thereby assisting decision-making processes in the tobacco industry.…”
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Evaluation of energy and protein intake and prediction of growth performance of growing-finishing pigs based on meta-analysis by DI Hanqiu, WANG Shanshan, ZHONG Yifan, CHEN Bin, WANG Haifeng

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An In Situ Characterisation Method for 3-D Electrospun Foams by Kyriakos Almpanidis, Chloe J. Howard, Vlad Stolojan

“…Finally, this fast in situ evaluation method can replace the post-fabrication time-consuming one. …”
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