Algorithms for Effector Prediction in Plant Pathogens and Pests: Achievements and Current Challenges by César De los Santos-Briones, Karla Gisel Carreón-Anguiano, Sara E. Vila-Luna, Jewel Nicole Anna Todd, Ignacio Islas-Flores, Luis Sáenz-Carbonell, Pablo Alejandro Gamas-Trujillo, Blondy Canto-Canché

Subjects: “…algorithms…”
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Extreme Gradient Boosting Algorithm for Predicting Shear Strengths of Rockfill Materials by Mahmood Ahmad, Ramez A. Al-Mansob, Kazem Reza Kashyzadeh, Suraparb Keawsawasvong, Mohanad Muayad Sabri Sabri, Irfan Jamil, Arnold C. Alguno

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Machine learning algorithms to predict the tensile strength of novel composite materials by S. Sathees Kumar, P. Shyamala, Pravat Ranjan Pati

“…Future studies will extend this methodology to multi-property prediction, integrating microstructural descriptors for improved real-world applicability.…”
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Differentially Private Clustered Federated Load Prediction Based on the Louvain Algorithm by Tingzhe Pan, Jue Hou, Xin Jin, Chao Li, Xinlei Cai, Xiaodong Zhou

“…The framework can train load-forecasting models with a fast convergence rate and better prediction performance than current mainstream federated learning algorithms.…”
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Neural network and Markov based combination prediction algorithm of video popularity by Xuesen MA, Shuyou CHEN, Xiangdong XU, Zhaokun CHU

“…Caching popular video into user-side in advance improves the user experience and reduces operator costs, which is a common practice in the industry.How to effectively predict the popularity of videos has become a hot issue in the industry.On account of the shortcomings of traditional prediction algorithms such as poor nonlinear mapping ability, low prediction accuracy and weak adaptability, a video popularity prediction algorithm based on a neural network and Markov combined model (Mar-BiLSTM) was proposed.Information dependencies were preserved by constructing bidirectional memory network model (bi-directional long short-term memory, BiLSTM), the prediction accuracy of the model was further improved by using Markov properties while avoiding the increase of the complexity of the model caused by the introduction of external variables.Experimental results show that compared with traditional time series and classic neural network algorithms, the proposed algorithm improves predicting accuracy, effectiveness and reduces the amount of calculation.…”
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The Ranking Prediction of NBA Playoffs Based on Improved PageRank Algorithm by Fan Yang, Jun Zhang

“…It is of great significance to predict the results accurately based on the statistics of sports competition for participants research, commercial cooperation, advertising, and gambling profit. …”
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Actionable predictions: How designers of algorithmic systems calibrate criminal futures by Maximilian Heimstädt, Simon Egbert

“…Hopes and fears about algorithmic predictions are often rooted in the assumption that they represent a particularly actionable form of knowledge. …”
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ISLRWR: A network diffusion algorithm for drug-target interactions prediction. by Lu Sun, Zhixiang Yin, Lin Lu

“…Notably, the ISLRWR algorithm improved the area under the receiver operating characteristic curve (AUROC) by 7.53 and 5.72%, and the area under the precision-recall curve (AUPRC) by 5.95 and 4.19% compared to the RWR and MHRW algorithms, respectively, in predicting DTIs performance. …”
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Smart Agriculture: Predicting Diseases in olive using Deep Learning Algorithms by Rahman F., Raghatate Kapesh Subhash

“…In this study, olive tree diseases are managed by improving prediction and management using a deep learning algorithm, with the aim of efficiency and accuracy of the process. …”
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Development and external validation of prediction algorithms to improve early diagnosis of cancer by J. Hippisley-Cox, CA Coupland

“…Abstract Cancer prediction algorithms are used in the UK to identify individuals at high probability of having a current, as yet undiagnosed cancer with the intention of improving early diagnosis and treatment. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

Subjects: “…Crayfish optimization algorithm…”
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FEATURE-BASED IMPLEMENTATION OF MACHINE LEARNING ALGORITHMS FOR CARDIOVASCULAR DISEASE PREDICTION by H. Singh, R. Tripathy, P. Kumar Sarangi, U. Giri, S. Kumar Mohapatra, N. Rameshbhai Amin

“…After applying all algorithms to our data set, the experimental results concluded that the Logistic Regression model has predicted well with highest accuracy of 92% in comparison with other algorithms.…”
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Comparative performance analysis of neoepitope prediction algorithms in head and neck cancer by Leila Y. Chihab, Leila Y. Chihab, Julie G. Burel, Aaron M. Miller, Aaron M. Miller, Luise Westernberg, Brandee Brown, Jason Greenbaum, Michael J. Korrer, Stephen P. Schoenberger, Sebastian Joyce, Sebastian Joyce, Young J. Kim, Zeynep Koşaloğlu-Yalçin, Bjoern Peters, Bjoern Peters

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Sustainable Selection of Machine Learning Algorithm for Gender-Bias Attenuated Prediction by Raik Orbay, Evelina Wikner

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Prediction of dialysis adequacy using data-driven machine learning algorithms by Yi-Chen Liu, Ji-Ping Qing, Rong Li, Juan Chang, Li-Xia Xu

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Application of machine learning algorithm to predict the behavior of stocks marketed in Brazil by Gabriel Donadio Costa, Rogério João Lunkes

“…This work analyzes the application of machine learning algorithms in the selection of portfolios in the Brazilian market. …”
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Prediction Model of Late Fetal Growth Restriction with Machine Learning Algorithms by Seon Ui Lee, Sae Kyung Choi, Yun Sung Jo, Jeong Ha Wie, Jae Eun Shin, Yeon Hee Kim, Kicheol Kil, Hyun Sun Ko

“…Two sets of variables from the first trimester until 13 weeks (E1) and the early third trimester until 28 weeks (T1) were used to develop the FGR prediction models using a machine learning algorithm. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

“…Once trained, these models can make predictions about future events or outcomes, such as the likelihood of a patient developing a particular disease, the risk of complications, or the effectiveness of treatment. …”
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Machine Learning Algorithms for Prediction of Survival Curves in Breast Cancer Patients by Roqia Saleem Awad Maabreh, Malik Bader Alazzam, Ahmed S. AlGhamdi

“…The main goal of this study is to find the best machine learning algorithms for predicting the individualised survival of breast cancer patients, as well as the most appropriate treatment, and to propose new numerical variable stratifications. …”
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Improved Backpropagation Using Genetic Algorithm for Prediction of Anomalies and Data Unavailability by Gunadi Widi Nurcahyo, Akbari Wafridh, Yuhandri

Subjects: “…data prediction…”
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