Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) by Min Tan, Jinjin Zhao, Yushun Tao, Uroosa Sehar, Yan Yan, Qian Zou, Qing Liu, Long Xu, Zeyang Xia, Lijuan Feng, Jing Xiong

“…Conclusion Machine learning algorithms can be used to identify ADCS among gastroenterology patients. …”
Get full text

Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms by Mengdi Liang, Yuelin Liu, Yue Huang, Ge Ma, Xu Han, Shuaikang Li, Jing Hang, Hui Xie, Lin Chen, Xiaoan Liu, Shui Wang, Tiansong Xia

“…Three machine learning algorithms were applied for feature selection. Then, all the selected features were used for the construction of the prediction model via four machine learning algorithms. …”
Get full text

Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

Get full text

Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…The GWO-SVM-SG1st model achieved the highest classification accuracy, with 94.641% on the prediction sets. This study showcases the potential of combining hyperspectral imaging with intelligent optimization algorithms, offering an effective solution for jujube variety classification.…”
Get full text

Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

Subjects: “…TN prediction…”
Get full text

A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms by Aihua Yu, Qingjie Xiao

“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. …”
Get full text

Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation by Hutan Ashrafian, Jessica Morley, Joe Zhang, Christopher Oddy

Get full text

Learning unbiased risk prediction based algorithms in healthcare: A case study with primary care patients by Vibhuti Gupta, Julian Broughton, Ange Rukundo, Lubna J. Pinky

“…Additionally, effective strategies are proposed to address gender, race, and age biases, ensuring that risk prediction outcomes are equitable and impartial. Through experiments with various machine learning algorithms leveraging the Fairlearn tool, we have identified biases in the dataset, compared the impact of these biases on the prediction performance, and proposed effective strategies to mitigate these biases. …”
Get full text

WCN25-867 BAYESIAN DEEP LEARNING ALGORITHMS TO PREDICT THE RATE OF DETERIORATION IN CHRONIC KIDNEY DISEASE by Laxmi Priya Kasi, Sujoy Kar, Sanjay Maitra, Tameem Ansari, Bharath Potla, Sangita Reddy

Get full text

Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea) by Degninou Yehadji, Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo

Get full text

PM2.5 concentration prediction using machine learning algorithms: an approach to virtual monitoring stations by Ahmad Makhdoomi, Maryam Sarkhosh, Somayyeh Ziaei

“…The ML models performed very well in predicting the concentrations of PM2.5 with around 95% of their predictions falling within the factor of the observed concentration. …”
Get full text

Use of responsible artificial intelligence to predict health insurance claims in the USA using machine learning algorithms by Ashrafe Alam, Victor R. Prybutok

“…Methods: Six ML algorithms were used to predict health insurance claims, and their performance was evaluated using various metrics. …”
Get full text

Leveraging Machine Learning Regression Algorithms to Predict Mechanical Properties of Evaporitic Rocks From Their Physical Attributes by Ayham Zaitouny, Hasan Arman, Anusuya Krishnan, Alaa Ahmed, Ahmed Gad

“…In this study, machine learning (ML) regression algorithms were applied to predict four key mechanical parameters, namely, uniaxial compressive strength (UCS), point load index (PLI), indirect tensile strength (ITS), and Schmidt hardness value (SHV), based on the physical attributes of evaporitic rocks. …”
Get full text

The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms by Hongxia Yan, Yixin Tan, Fan Qiao, Zhuotong Zeng, Yaqian Shi, Xueqin Zhang, Lu Li, Ting Zeng, Yi Zhan, Ruixuan You, Xinglan He, Rong Xiao, Xiangning Qiu

Subjects: Get full text

Development and Validation of a Neonatal Hypothermia Prediction Model for In-Hospital Transport Using Machine Learning Algorithms: A Single-Center Retrospective Study by Zhang W, Gu X, Gu C, Yao L, Zhang Y, Wang K

“…Six machine learning algorithms—Decision Tree (DT), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Artificial Neural Network (ANN), and Naive Bayes (NB)—were used to develop predictive models. …”
Get full text

Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks by Naveen GARG, Siddharth DHRUW, Laghu GANDHI

“…The paper presents the application of Artificial Neural Networks (ANN) in predicting sound insulation through multi-layered sandwich gypsum partition panels. …”
Get full text

Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm... by Paolo Iván Cubillo-Leyton, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña

Get full text

Improved performance of single sided axial flux for reduction in cogging torque (IMPACT) by Ahmed Dawood, Junaid Ikram, Muhammad Bilal Riaz, Khurram Saleem Alimgeer, Shumaila Javeed

Get full text

Unleashing Predicting a Comparative Study of Machine Learning for Bankruptcy Risk Prediction by Yupeng Li, Ke Sun

“…Predictive analytics are advanced through the utilization of sophisticated machine learning methodologies, specifically the Random Forest classification model (RFC), The Grasshopper Optimizer Algorithm (GOA), and the Artificial Rabbits Optimizer (ARO). …”
Get full text

Excavating trajectory planning of electric shovel based on dynamic excavating volume prediction by Juan Wu, Rui Liu, Baoguo Lin

Get full text