Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data. by Tian Xia, Lanju Zhou, Khalil Ahmad

“…The 93% precision demonstrated an excellent match for the most effective prediction model, linear dipole testing. Furthermore, the "good fit" of the model was verified by its achieved area-under-the-curve ratios of 0.97 for abnormal identification and 0.96 for daily detection.…”
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Short-term photovoltaic power prediction combination model considering seasonal characteristic and data window by ZHANG Jing, XIONG Guojiang

Subjects: “…short-term photovoltaic power prediction…”
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Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

“…Abstract Accurate prediction of drug–target interactions is critical for advancing drug discovery. …”
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Thermal Distribution Mapping and Its Role in Informing Fatigue Life Predictions of FRP Patrol Vessels by Rachman Daudy Kevinaura, Zubaydi Achmad, Ismail Abdi, Ariesta Rizky Chandra, Pratikno Herman, Putra Nicky Rahmana, Murwatono Totok Triputrastyo

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Time Series Analysis: Application of LSTM model in predicting PM 2.5 concentration in Beijing by Yang Rui

“…Air pollution forecasting for public health and policy-making has a critical importance, this paper employs a Long Short-Term Memory (LSTM) model to perform in-depth prediction of PM2.5 concentrations measured at the U.S. …”
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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

“…The goal of this research is to first develop an accurate ensemble model for prediction of unseen cases of CKD given the biomarkers. …”
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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

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A Nomogram for Predicting Overall Survival in Primary Central Nervous System Lymphoma: A Retrospective Study by Ling Y, Miao X, Zhou X, Ma J, Lin Z, Li Q, Zhang M, Ma Y, Chen B

“…The novel prognostic model also provided superior risk stratification for patients with PCNSL compared with existing scoring systems.Conclusion: This study presents a novel prognostic model for predicting the OS of patients with newly diagnosed PCNSL. …”
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Development of a nomogram for predicting pancreatic portal hypertension in patients with acute pancreatitis: a retrospective study by Yong Lv, Hui Luo, Yingjie Zhang, Xiangping Wang, Yanglin Pan, Yunling Li, Qiaoyu Su, Xianchen Zhan, Linhui Zhang, Xiaoyu Kang, Shuhui Liang, Gui Ren

“…This study aims to develop and validate a nomogram to predict PPH in patients with AP.Methods Consecutive patients with AP from 2015 to 2023 were retrospectively included in the study. …”
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Life prediction analysis of patrol vessel made from FRP with variations of wave height and wave direction by Octaviano Noel, Zubaydi Achmad, Ismail Abdi, Ariesta Rizky Chandra, Pratikno Herman, Rahmana Putra Nicky, Triputrastyo Murwatono Totok

Subjects: “…life prediction…”
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Predicting Postoperative Re-Tear of Arthroscopic Rotator Cuff Repair Using Artificial Intelligence on Imbalanced Data by Zhibin Zhang, Zhewei Zhang, Zhaoxiang Peng, Yihong Dong

“…Retears after rotator cuff surgery are a common complication. Accurate prediction of retear is essential to minimise the risk of retear. …”
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Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model by Yi Zhang, Pengtao Liu, Yingying Xu, Meng Zhang

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Reasons why osteoarthritis predicts mortality: path analysis within a Cox proportional hazards model by George Peat, Martin J Thomas, Milica Blagojevic-Bucknall, Ross Wilkie, Simran Singh Parmar, Diane Smith, Bethany Jane Seale, Gemma Mansell

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Comparison of 2-D and 3-D Analysis of Running Kinematics and Actual Versus Predicted Running Kinetics by Caitlyn Martinez, Seth Garbett, Kristen Hiromasa, Rhandi Jackson, Eric Miya, Michelle Miya, Joshua D White, Brian S Baum, Mark F Reinking

“…# Background Providing clinicians with an accurate method to predict kinetic measurements using 2D kinematic motion analysis is crucial to the management of distance runners. …”
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Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data by Mihkel Kotli, Geven Piir, Uko Maran

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Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques by Nang Xuan Ho, Tien-Thinh Le, The-Hung Dinh, Van-Hai Nguyen

“…Abstract This article deals with prediction of buckling damage of steel equal angle structural members using a surrogate model combining machine learning and metaheuristic optimization technique. …”
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Aberrant SNHG expression predicts poor prognosis in esophageal cancer using meta-analysis and bioinformatics analysis by Ke Shi, Li-De Huang, Dan Li, Wei-Min Luo, Hua-Song Liu, Dong-Xiao Ding, Qiang Guo, Yue-Feng Liu

“…In populations with low expression of SNHG2, SNHG5, and SNHG12, increasing SNHG expression predicted a favorable cancer prognosis (HR: 0.511, 95%CI = 0.322-0.700). …”
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To construct and validate a risk score model of angiogenesis-related genes to predict the prognosis of hepatocellular carcinoma by Duangui Gao, Yuan Lu, Tianpeng Jiang, Qinghong Duan, Zhi Huang

“…The GSVA analysis suggested that the predicted high-risk population showed higher activity in the purine, pyrimidine, and riboflavin metabolic pathways. …”
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Predictive value of Frank’s sign for obstructive coronary artery disease confirmed by coronary computed tomography angiography by Truong Phi Hung, Nguyen Minh Kha, Dang Tuong Vi, Tran Trong Nhan, Hoang Van Sy

“…Frank’s sign demonstrated an area under the curve of 0.69, with 88% sensitivity and 50% specificity in predicting CAD. This study highlights a significant association between Frank’s sign and CAD, independent of established risk factors, in a Vietnamese population. …”
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Histological risk score and its role in predicting recurrence in early-stage oral squamous cell carcinomas by Daphne Fonseca, Rashmi Khemani, Mohan K. Pasam, Ravindranath Tagore, B. Vishal Rao, Suseela Kodandapani, Chandrasekhara Rao, K. V. V. N. Raju, T Subramanyeshwar Rao

“…Conclusion: Adequate assessment of simple parameters on routine H and E by incorporating Brandwein-Gensler histological risk scoring model at the initial presentation can help prognosticate and predict LRR and select patients for post-surgical adjuvant therapy.…”
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