The TB27 Transcriptomic Model for Predicting Mycobacterium tuberculosis Culture Conversion by Maja Reimann, Korkut Avsar, Andrew DiNardo, Torsten Goldmann, Gunar Günther, Michael Hoelscher, Elmira Ibraim, Barbara Kalsdorf, Stefan Kaufmann, Niklas Köhler, Anna Mandalakas, Florian Maurer, Marius Müller, Dörte Nitschkowski, Ioana Olaru, Cristina Popa, Andrea Rachow, Thierry Rolling, Helmut Salzer, Patricia Sanchez-Carballo, Maren Schuhmann, Dagmar Schaub, Victor Spinu, Elena Terhalle, Markus Unnewehr, Nika Zielinski, Jan Heyckendorf, Christoph Lange

“…Methods: Using a multi-step machine learning algorithm to identify an RNA-based algorithm to predict the remaining time to culture conversion at flexible time points during anti-tuberculosis therapy.  …”
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Human Heart Disease Prediction System Using Data Mining Techniques by Sidra Javed, Hamza Javed, Ayesha Saddique, Beenish Rafiq

“…To address this problem, Decision Tree is used to predict the heart disease. In this study the collected data is pre-processed, Decision Tree algorithm and ID3 were then applied to predict the heart disease.   …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Hysteretic curve characteristics in rectangular shear walls predicted by machine learning by Jungui Dong, Ce Chen

“…An interpretable empirical guidance machine learning (IEG-ML) was proposed for predicting these feature points. IEG-ML aligns with empirical trends from extensive experiments and is explainable via explicit formulas. …”
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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…With the development of financial technology, the traditional experience-based and single-network credit default prediction model can no longer meet the current needs. …”
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A Local–Global Graph KAN for Multi‐Class Prediction of PPI by Minghui Liu, Ying Qu

“…Therefore, using machine learning to treat multiple PPI predictions as binary classifications has become an alternative, but there is a problem of data imbalance. …”
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An Inference Framework of Markov Logic Network for Link Prediction in Heterogeneous Networks by Zhongbin Li, Kun Yue, Lixing Yu, Jiahui Wang

“…The presence of multiplex edges and sparse links often hampers the efficacy of link prediction (LP) tasks. By harnessing the expressive power of Markov logic network (MLN) formulations, multiplex edges can be unified to enhance LP effectiveness. …”
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Prediction of Train Arrival Delay Using Hybrid ELM-PSO Approach by Xu Bao, Yanqiu Li, Jianmin Li, Rui Shi, Xin Ding

“…Next, an ELM with one hidden layer is developed to predict train arrival delays by considering these characteristics mentioned before as input features. …”
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Modelling and Prediction of Random Delays in NCSs Using Double-Chain HMMs by Yuan Ge, Yan Zhang, Wengen Gao, Fanyong Cheng, Nuo Yu, Jincenzi Wu

“…This paper is concerned with the modelling and prediction of random delays in networked control systems. …”
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Automatic determination of the frequency behaviour of the larynx tone by the method of linear prediction by Andrzej DZIURNIKOWSKI

“…This paper presents a method of automatically tracing the frequency of the larynx tone, based on a numerical implementation of the method of linear prediction on a digital computer. It also discusses the algorithm for the practical implementation of this method, derived by the author, and presents the results obtained from the analysis of a continuous speech signal with a duration of approximately 2 seconds.…”
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The Impact of Prediction Models on Energy-Aware Resource Management in FaaS Platforms by Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto

“…Moreover, resource allocation performed through the EA-RM algorithm reduces the energy consumption by ~12-45% on average w.r.t. competitors, and is proven to be more robust w.r.t. the accuracy of the prediction model used.…”
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Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The ANN was tested on independent data and demonstrated exceptional performance, achieving 96% accuracy for effective porosity and 98% for permeability predictions in sandstone formations. This efficient algorithm eliminates the need for core sample analysis, reducing costs and time while improving prediction reliability, making it a valuable tool for subsurface characterization and resource exploration.…”
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Development and Validation of a Dynamic Prediction Model for Massive Hemorrhage in Trauma by Chengyu Guo, Maolin Tian, Minghui Gong, Fei Pan, Hui Han, Chunping Li, Tanshi Li

“…This study developed and validated a group of dynamic prediction models based on vital sign time-series data and a deep-learning algorithm to assist medical staff in the early diagnosis and dynamic prediction of a future massive hemorrhage in trauma.…”
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An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…Abstract To address the issue of serious inefficiency in the traditional manual evaluation methods of rock core integrity, a deep learning-based algorithm named IDA-RCF (Intelligent detection algorithm for Rock Core Fissure) is proposed in this paper, which realizes the automatic evaluation of rock core integrity in accordance with the fissure identification results. …”
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CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer by Manman LI, Yigang FU, Yong XIAO, Wang CHEN, Feng FENG, Guodong XU

“…Objective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). …”
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Use Self-Training Random Forest for Predicting Winter Wheat Yield by Yulin Shen, Benoît Mercatoris, Qingzhi Liu, Hongxun Yao, Zongpeng Li, Zhen Chen, Wensheng Wang

“…The effectiveness of supervised ML heavily depends on having a large, accurate, and diverse annotated dataset, which poses a challenge in applying ML for yield prediction. To address this issue, we developed a self-training random forest algorithm capable of automatically expanding the annotated dataset. …”
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Convolution of the physical point cloud for predicting the self-assembly of colloidal particles by Seunghoon Kang, Young Jin Lee, Kyung Hyun Ahn

“…This paper presents a novel algorithm for predicting the kinetic and thermodynamic pathways of colloidal systems. …”
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Fast Prediction for Roll Motion of a Damaged Ship Based on SVR by LIU Han, SU Yan, ZHANG Guoqiang

“…Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.…”
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