EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals by Aidan H. Lakshman, Erik S. Wright

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A supervised machine learning approach with feature selection for sex-specific biomarker prediction by Luke Meyer, Danielle Mulder, Joshua Wallace

“…Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algorithms remains a concern. …”
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Development and Validation of an AI-Based Risk Prediction Model for Osteoporosis in Post-Menopausal Women by Juhi Deshpande, Chanchal Kumar Singh

“…The aim is to develop and validate an AI-based predictive model for osteoporosis in postmenopausal women. …”
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A Review on Fall Prediction and Prevention System for Personal Devices: Evaluation and Experimental Results by Masoud Hemmatpour, Renato Ferrero, Bartolomeo Montrucchio, Maurizio Rebaudengo

“…Kinematic features obtained from the data collected from accelerometer and gyroscope have been evaluated in combination with different machine learning algorithms. An experimental analysis compares the evaluated approaches by evaluating their accuracy and ability to predict and prevent a fall. …”
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Prediction of Spontaneous Protein Deamidation from Sequence-Derived Secondary Structure and Intrinsic Disorder. by J Ramiro Lorenzo, Leonardo G Alonso, Ignacio E Sánchez

“…Compared to previous algorithms, NGOME does not require three-dimensional structures yet yields better predictions than available sequence-only methods. …”
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Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model by Tianjiao Li

“…At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.…”
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A probabilistic gap based condition prediction approach for desulfurization slurry circulating pump by Jiaxing Zhu, Buyun Sheng, Junlan Hu, Yanfei Li, Ruiping Luo, Yue Shi

“…The Desulfurization Slurry Circulation (DSC) Pump is crucial for controlling gas emissions in limestone-gypsum wet flue gas desulfurization (WFGD) power plants. However, predicting the condition of DSC pumps is hindered by a lack of samples, obstructing field development. …”
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Comparing Models and Performance Metrics for Lung Cancer Prediction using Machine Learning Approaches. by Ruqiya, Noman Khan, Saira Khan

“…It optimizes the performance of models for predicting lung cancer. …”
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Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments by Ray Colucci, Imad Mahgoub

“…Using satellite data from weather sensors, we trained machine learning models to enhance solar irradiance predictions. We evaluated five popular machine learning algorithms and applied ensemble methods, achieving a substantial improvement in predictive accuracy. …”
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Using machine learning techniques for DSP software performance prediction at source code level by Weihua Liu, Erh-Wen Hu, Bogong Su, Jian Wang

“…Therefore, we propose a new algorithm called MAX/MIN algorithm to select the best-predicted execution time. …”
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Shoulder–Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration by Siyu Zong, Wei Li, Dawen Sun, Zhuoda Jia, Zhengwei Yue

“…To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). …”
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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This research contributes valuable insights to financial analysts and investors in identifying high-growth firms and underscores the potential of machine learning in economic prediction.…”
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Preeclampsia pathogenesis and prediction - where are we now: the focus on the role of galectins and miRNAs by Natasa Karadzov Orlic, Ivana Joksić

“…Preeclampsia is a complex, progressive multisystem hypertensive disorder during pregnancy that significantly contributes to increased maternal and perinatal morbidity and mortality. Two screening algorithms are in clinical use for detecting preeclampsia: first-trimester screening, which has been developed and validated for predicting early-onset preeclampsia but is less effective for late-onset disease; and the sFlt-1:PlGF biomarker ratio (soluble tyrosine kinase and placental growth factor) used in suspected cases of preeclampsia. …”
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Renewable Generation (Wind/Solar) and Load Modeling through Modified Fuzzy Prediction Interval by Syed Furqan Rafique, Zhang Jianhua, Rizwan Rafique, Jing Guo, Irfan Jamil

“…In this paper, an improved fuzzy prediction horizon forecasting method is developed to address the issue of intermittence and uncertainty problem related to renewable generation and load forecast. …”
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Stock Price Prediction Using Machine Learning: Evidence from Pakistan Stock Exchange by Zafar Akhter, Dr. Hassan Raza

“…The application of a Random Forest classifier is utilized on a dataset including historical stock prices (namely, the KSE-100 Index) to generate predictions regarding the future movement of stocks, specifically whether they would experience an increase or decrease. …”
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An Augmented AutoEncoder With Multi-Head Attention for Tool Wear Prediction in Smart Manufacturing by Chunping Dong, Jiaqiang Zhao

“…The result validates the superior performance of the proposed model compared to other deep learning algorithms in predicting tool wear.…”
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Dimensions management of traffic big data for short-term traffic prediction on suburban roadways by Arash Rasaizadi, Fateme Hafizi, Seyedehsan Seyedabrishami

“…In this study, big traffic data were used to predict traffic state on a section of suburban road from Karaj to Chalous located in the north of Iran. …”
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Dielectric tensor prediction for inorganic materials using latent information from preferred potential by Zetian Mao, WenWen Li, Jethro Tan

“…This study leverages multi-rank equivariant structural embeddings from a universal neural network potential to enhance predictions of dielectric tensors. We develop an equivariant readout decoder to predict total, electronic, and ionic dielectric tensors while preserving O(3) equivariance, and benchmark its performance against state-of-the-art algorithms. …”
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Ecotoxicity prediction of chemical compounds using machine learning and different molecular structure representations by Michał Marek, Rafał Kurczab

“…This paper presents the development of models for predicting chemical ecotoxicity (HC50) based on machine learning algorithms and different molecular representations. …”
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Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks by Reham Abdallah, Sayed Abdelgaber, Hanan Ali Sayed

“…The researchers adopt the Analytic Hierarchy Process (AHP) for feature selection and integrated transfer learning to boost the accuracy of the study’s predictions. The researchers’ approach involves the deployment of several machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, and an ensemble of these methods. …”
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