Identification of m6A methyltransferase-related WTAP and ZC3H13 predicts immune infiltrates in glioblastoma by Liyun Gao, Jiaxin Gao, Jiayin He, Wenyan Fan, Xiangxin Che, Xin Wang, Tao Wang, Chunhua Han

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Feature engineering on climate data with machine learning to understand time-lagging effects in pasture yield predictionGitHub by Thirunavukarasu Balasubramaniam, Wathsala Anupama Mohotti, Kenneth Sabir, Richi Nayak

“…Pastures are a primary food source for livestock in Australia, with various pasture species grown in rotations. Accurate prediction of pasture availability is critical for effective farm management, livestock growth, and maintaining the supply chain. …”
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Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

“…IntroductionMachine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. …”
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Development and Cross-Validation of Anthropometric Predictive Equations to Estimate Total Body Fat Percentage in Adult Women in Sri Lanka by Nirmala Rathnayake, Gayani Alwis, Janaka Lenora, Sarath Lekamwasam

“…This study was designed to develop and cross-validate anthropometric predictive equations to estimate the total body fat percentage (TBFP) of Sri Lankan adult women. …”
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Anti-Apolipoprotein A-1 IgG Levels Predict Coronary Artery Calcification in Obese but Otherwise Healthy Individuals by Alessandra Quercioli, Fabrizio Montecucco, Katia Galan, Osman Ratib, Pascale Roux-Lombard, Sabrina Pagano, François Mach, Thomas H. Schindler, Nicolas Vuilleumier

“…In conclusion, those preliminary results indicate that anti-apoA-1 IgG autoantibodies are raised in obese subjects and independently predict the presence of coronary calcification in this population but not the presence of coronary endothelial dysfunction.…”
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LABORATORY ELECTROCHEMISTRY “MYSTERY BOX”: FROM PRE-SERVICE TEACHERS’ OBSERVATIONS TO INFERENCES THROUGH PREDICT-OBSERVE-EXPLAIN STRATEGY by Carla Morais, Cidália André, Joana Alves, Gildo Girotto Jr.

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Assisting significance of lncRNA ASB16-AS1 in the early detection and prognosis prediction of patients with deep venous thrombosis by Menglan Li, Yingying Li, Dawei Zhang, Cheng Cheng, Meiying Yang, Xiuyin Zhang, Xinming Yu, Bo Lu, Min Wang

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A CRITIC-BPNN APPROACH TO FRICTION STIR WELDING PARAMETRIC SELECTION AND PREDICTION USING AA6082-T6 MATERIAL by Mufutau Adeniyi Abolarin, Adeyinka Oluwo, John Rajan, Swaminathan Jose, Sunday Ayoola Oke |, Alexander Iwodi Agada, Ayomide Sunday Ibitoye

“…For the 4-1-2 neural network architecture, the values of the ultimate tensile strength and percentage elongation at the optimal thresholds are 0.6457 and 0.6019, respectively, for the first forward pass and 0.6123 and 0.6356, respectively, for the second forward pass. The predicted tensile strength is 320.64 MPa and the prediction for the percentage elongation is 18.83%. …”
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Assessing the Impact of Modified Initial Abstraction Ratios and Slope Adjusted Curve Number on Runoff Prediction in the Watersheds of Sulaimani Province. by Farhan Ahmad Abdulrahman, Tarq Hama Karim

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Phase diagram prediction and particle characterization of Sn-Ag nano alloy for low melting point lead-free solders by Sopousek J., Vrestal J., Zemanova A., Bursi J.

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Comparative Analysis of pKa Predictions for Arsonic Acids Using Density Functional Theory-Based and Machine Learning Approaches by Miroslava Nedyalkova, Diana Heredia, Joaquín Barroso-Flores, Marco Lattuada

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Correlation between antenatal and postnatal coiling index and its role in prediction of perinatal outcome: A prospective cohort study by Ankita Kumari, Vani Aditya, Shaila Mitra, Garima Maurya, Pratima Sharma, Harish Chandra Tiwari

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Treatment of Neovascular Age-Related Macular Degeneration with Anti-VEGF Agents: Predictive Factors of Long-Term Visual Outcomes by Ana Catarina Pedrosa, Tiago Sousa, João Pinheiro-Costa, João Beato, Manuel S. Falcão, Fernando Falcão-Reis, Angela Carneiro

“…Purpose. To evaluate the predictive factors of long-term visual outcomes in neovascular age-related macular degeneration (nAMD) treated with antivascular endothelial growth factor (anti-VEGF) agents. …”
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Predicting breast cancer prognosis using PR and PIK3CA biomarkers: a comparative analysis of diagnostic groups by Yuting Feng, Qingzhen Song, Lei Yan, Ruoqi Li, Mengqin Yang, Peng Bu, Jing Lian

“…Additionally, a risk prediction model was developed using the PR expression level and PIK3CA mutation status. …”
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A logistic regression model to predict long-term survival for borderline resectable pancreatic cancer patients with upfront surgery by Jin-Can Huang, Shao-Cheng Lyu, Bing Pan, Han-Xuan Wang, You-Wei Ma, Tao Jiang, Qiang He, Ren Lang

“…There still has been a debate about which predictive strategy is better in patients with borderline resectable pancreatic cancer (BRPC). …”
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A Nomogram Built on Clinical Factors and CT Attenuation Scores for Predicting Treatment Response of Acute Myeloid Leukemia Patients by Linna Liu, Wenzheng Lu, Li Xiong, Han Qi, Robert Peter Gale, Bin Yin

“…While clinical factors such as age and genetic mutations contribute to prognosis, recent studies suggest that CT attenuation scores may also predict treatment outcomes. This study aims to develop a nomogram combining clinical and CT-based factors to predict treatment response and guide personalized therapy for AML patients. …”
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Structural Response Prediction of Floating Offshore Wind Turbines Based on Force-to-Motion Transfer Functions and State-Space Models by Jie Xu, Changjie Li, Wei Jiang, Fei Lin, Shi Liu, Hongchao Lu, Hongbo Wang

Subjects: “…wave frequency response prediction…”
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Prediction of Lift Coefficient for Tandem Wing Configuration or Multiple-Lifting-Surface System Using Prandtl’s Lifting-Line Theory by Hao Cheng, Hua Wang

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Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review by Victoria Moglia, Owen Johnson, Gordon Cook, Marc de Kamps, Lesley Smith

“…Prediction windows and lead times varied greatly between studies, even for models predicting the same cancer. …”
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A Model Predictive Control Framework for Combining Energy Arbitrage and Power Quality Applications From Energy Storage Systems by Ujjwol Tamrakar, Niranjan Bhujel, Tu A. Nguyen, Raymond H. Byrne, Babu Chalamala

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