A Hybrid GAS-ATT-LSTM Architecture for Predicting Non-Stationary Financial Time Series by Kevin Astudillo, Miguel Flores, Mateo Soliz, Guillermo Ferreira, José Varela-Aldás

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Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques by Hong Xiao, Yi-lang Ding, Chao Wang, Peng Yang, Qiang Chen, Hao-nan He, Ruijie Yao, Hai-lin Huang, Xi Chen, Mao-yuan Wang, Song-xi Tang, Hui-liang Zhou

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Solitaire stent retriever failure during thrombectomy: is there any image that can predict non-recanalization? by Igor PAGIOLA, Bruno AMARAL, Celso SAITO, Dárcio NALLI, Henrique CARRETE JUNIOR, Michel Eli FRUDIT

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Utilizing T-Lymphocyte Activation-Related Cytokines to Predict Non-Responsiveness to Treatment in Pediatric Kawasaki Disease by Ye B, Xiao J, Zhang C

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A nomogram for predicting non-curative resection in patients with early gastric cancer based on white light imaging by Mengyu Cao, Linlin Ren, Congcong Min, Zeyuan Diao, Hao Chen, Hua Liu, Xiaoyu Li, Jiahui Xu, Zibin Tian, Tao Mao

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WCN24-1295 Prevalence and factors predicting non diabetic kidney disease in type 2 diabetic patients by Jasmine Sethi, Vignesh Subramani, Vaishnavi Venkatasubramanian, Manish Rathi

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Living alone predicts non-home discharge post elective hip arthroplasty: A matched-pair cohort study by Benjamin K. Agnor, Ziyad O. Knio, Zhiyi Zuo

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Living alone predicts non-home discharge post elective hip arthroplasty: A matched-pair cohort study. by Benjamin K Agnor, Ziyad O Knio, Zhiyi Zuo

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Performance of different dynamic oxygenation indices incorporating heart rate to predict non-invasive ventilation outcomes in hypoxemic respiratory failure by Omnia Mohamed Mamdouh, Ashraf El Sayed Ahmed, Ahmed Zidan Abuzeid Hashem, Hadeer Ahmed Elshahaat

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Does academic excellence predict non-cognitive competencies? Insights from a situational judgement test among medical students in Nigeria by Ifunanya Clara Agu, Uche Shalom Obi, Chinyere Ojiugo Mbachu, Adanna Chukwuma

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Integrating Machine Learning and Deep Learning for Predicting Non-Surgical Root Canal Treatment Outcomes Using Two-Dimensional Periapical Radiographs by Catalina Bennasar, Antonio Nadal-Martínez, Sebastiana Arroyo, Yolanda Gonzalez-Cid, Ángel Arturo López-González, Pedro Juan Tárraga

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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

“…This study aims to predict 6-month non-remission in 222 disease-modifying anti-rheumatic drug (DMARD)-naïve RA patients initiating methotrexate monotherapy, using baseline patient characteristics from the ARCTIC trial.MethodsMachine learning models were developed utilizing twenty-one baseline demographic, clinical and laboratory features to predict non-remission according to ACR/EULAR Boolean, SDAI and CDAI criteria. …”
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Modeling and Predicting Time Series with Non-stationarity and Volatility by FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning

Subjects: “…time series prediction; non-stationarity; high volatility; long short-term memory neural network; multi-head self-attention…”
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Finite family groups for fermionic and leptoquark mixing patterns by Jordan Bernigaud, Ivo de Medeiros Varzielas, Jim Talbert

“…Assuming experimentally interesting CKM and PMNS matrix elements, our algorithm finds an abundance of predictive non-Abelian flavour groups and therefore provides promising directions for future model building in the flavoured leptoquark space, regardless of whether the anomalous R K ∗ $$ {\mathcal{R}}_{K^{\left(\ast \right)}} $$ measurements withstand further experimental scrutiny.…”
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The Emerging Biomarkers in Chronic Obstructive Pulmonary Disease: A Narrative Review by Kaitlin M. Phillips, Philip F. Lavere, Nicola A. Hanania, Muhammad Adrish

“…The fraction of exhaled nitric oxide (FENO) is increasingly studied in eosinophilic COPD endotypes and can be a diagnostic and predictive non-invasive biomarker. Imaging biomarkers, especially the quantitative computerized tomography (QCT) assessment of airway remolding, functional small airway disease, air trapping, lung function, and volume surrogates, all serve as non-invasive biomarkers for screening, early detection, and disease progression. …”
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A Novel In Vitro Primary Human Alveolar Model (AlveolAir™) for H1N1 and SARS-CoV-2 Infection and Antiviral Screening by Cindia Ferreira Lopes, Emilie Laurent, Mireille Caul-Futy, Julia Dubois, Chloé Mialon, Caroline Chojnacki, Edouard Sage, Bernadett Boda, Song Huang, Manuel Rosa-Calatrava, Samuel Constant

“…The differences between animal models and humans contribute to inefficiencies in drug development, highlighting the need for more relevant and predictive, non-animal models. In this context, AlveolAir™, a fully primary in vitro 3D human alveolar model, was characterized and demonstrated the sustained presence of alveolar type I (ATI) and type II (ATII) cells. …”
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Childhood adversity as a predictor of non-adherence to statin therapy in adulthood. by Maarit Jaana Korhonen, Jaana I Halonen, M Alan Brookhart, Ichiro Kawachi, Jaana Pentti, Hasse Karlsson, Mika Kivimäki, Jussi Vahtera

“…<h4>Purpose</h4>To investigate whether adverse experiences in childhood predict non-adherence to statin therapy in adulthood.…”
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CT radiomics identifying non‐responders to neoadjuvant chemoradiotherapy among patients with locally advanced rectal cancer by Zinan Zhang, Xiaoping Yi, Qian Pei, Yan Fu, Bin Li, Haipeng Liu, Zaide Han, Changyong Chen, Peipei Pang, Huashan Lin, Guanghui Gong, Hongling Yin, Hongyan Zai, Bihong T. Chen

“…Conclusion Pretreatment CT radiomics achieved satisfying performance in predicting non‐response to nCRT and could be helpful to assist in treatment planning for patients with LARC.…”
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Enzyme promiscuity shapes adaptation to novel growth substrates by Gabriela I Guzmán, Troy E Sandberg, Ryan A LaCroix, Ákos Nyerges, Henrietta Papp, Markus de Raad, Zachary A King, Ying Hefner, Trent R Northen, Richard A Notebaart, Csaba Pál, Bernhard O Palsson, Balázs Papp, Adam M Feist

“…After as few as approximately 20 generations, evolved populations repeatedly acquired the capacity to grow on five predicted non‐native substrates—D‐lyxose, D‐2‐deoxyribose, D‐arabinose, m‐tartrate, and monomethyl succinate. …”
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Impact of the “L” score from the RENAL nephrometry score on RAPN surgical outcomes in medial versus lateral renal tumors by Yasuhiro Numata, Hiroki Ito, Seiichiro Honda, Kota Kobayashi, Ryosuke Jikuya, Tomoyuki Tatenuma, Go Noguchi, Daiki Ueno, Mitsuru Komeya, Yusuke Ito, Kentaro Muraoka, Kazuki Kobayashi, Hisashi Hasumi, Kazuhide Makiyama

“…In medial tumors, the “L” score independently predicted non-achievement of trifecta (P = 0.011) and pentafecta (P = 0.032). …”
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