Prediction of in-hospital mortality in patients aged 75 years and older with acute ST-segment elevation myocardial infarction using logistic regression and classification tree by K. G. Pereverzeva, S. S. Yakushin

“…Mortality of 83,3% was predicted in patients without CS and without VT with a history of HF, WBC count ≥14,5×109/L and body mass index ≤23,7 kg/m2. …”
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Classification of Moral Decision Making in Autonomous Driving: Efficacy of Boosting Procedures by Amandeep Singh, Yovela Murzello, Sushil Pokhrel, Siby Samuel

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An Analytical Mathematical Study of Artificial Neural Network Algorithms in the Suitability of a Model for Medical Diagnosis by Omar Qasim, Israa Mohammed

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Machine Learning-Based Classification of Suspension Droplet-Solid Wall Impacts for Control of Droplet Fragmentation by Mikhail Vulf, Dmitry Zharikov, Dmitry Kolomenskiy, Dmitry Eskin, Pavel Osinenko

“…The models allow prediction of no-fragmentation outcomes, important for droplet-based 3D-printing and coating. To the best of our knowledge, this is the first study to use ML for the classification of suspension drop-wall impacts, including data from experiments with both heavier and lighter-than-liquid particles and inclined surfaces. …”
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Machine Learning Prediction of Tritium‐Helium Groundwater Ages in the Central Valley, California, USA by Abdullah Azhar, Indrasis Chakraborty, Ate Visser, Yang Liu, Jory Chapin Lerback, Erik Oerter

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A parsimonious model for classifying the traffic state of urban road networks: A two-stage regression approach by Wei Huang, Dalin Tang, Xin Qiao, Guojun Chen

“…The classification results are then compiled to conduct the subsequent regression analysis. …”
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Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression by Chaitanya Pallerla, Yihong Feng, Casey M. Owens, Ramesh Bahadur Bist, Siavash Mahmoudi, Pouya Sohrabipour, Amirreza Davar, Dongyi Wang

“…In NAS-WD, NAS was first used to automatically optimize the network architecture and hyperparameters. The classification results show that NAS-WD can classify the three WB levels with an overall accuracy of 95 %, outperforming the traditional machine learning model, and the regression correlation between the spectral data and hardness was 0.75, which performs significantly better than traditional regression models.…”
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EEG Signal Prediction for Motor Imagery Classification in Brain–Computer Interfaces by Óscar Wladimir Gómez-Morales, Diego Fabian Collazos-Huertas, Andrés Marino Álvarez-Meza, Cesar German Castellanos-Dominguez

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Multivariate analysis of Côte d’Ivoire consumer price index: linear, regularized and generalized regression approaches by Aubin Yao N’Dri, Auguste Konan Kouakou, Amadou Kamagaté, Ouagnina Hili

“…This paper seeks to explain this issue using Principal Component Analysis (PCA), Hierarchical Ascending Classification (HAC), as well as linear, regularized (Lasso, Ridge, Elastic Net), and generalized regression. …”
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Research on Tongue Image Segmentation and Classification Methods Based on Deep Learning and Machine Learning by Bin Liu, Zeya Wang, Kang Yu, Yunfeng Wang, Haiying Zhang, Tingting Song, Hao Yang

“…The proposed framework consists of three main components: tongue image segmentation, pixel-wise classification, and tongue color classification. …”
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Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction by Emmanuel Onah, Uche Jude Eze, Abdullahi Salahudeen Abdulraheem, Ugochukwu Gabriel Ezigbo, Kosisochi Chinwendu Amorha, Fidele Ntie-Kang

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Advanced Machine Learning for Preschooler Magnetic Resonance Imaging Analysis in Classification of Anxiety Disorders by Salik Mian, Pranav Kunderu, Shivm Patel

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Heart Rate Detection and Classification from Speech Spectral Features Using Machine Learning by Mohammed USMAN, Mohammed ZUBAIR, Zeeshan AHMAD, Monji ZAIDI, Thafasal IJYAS, Muneer PARAYANGAT, Mohd WAJID, Mohammad SHIBLEE, Syed Jaffar ALI

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Novel multifractal-based classification model for the quality grades of surrounding rock within tunnels by Junjie Ma, Tianbin Li, Zhen Zhang, Roohollah Shirani Faradonbeh, Mostafa Sharifzadeh, Chunchi Ma

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Estimating Parameters and Predicting the Risk of MiscarriageInfertility, and Psychological Disorders Among Chemical Attack Survivors of Kurdistan by Using Multinomial Logistic Regr... by Nazeera Sedeek Kareem Al Barznji

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Models for forecasting flight delays by D. Tarasonok, Y. Oliinyk, T. Likhouzova

“…The purpose of the work is to predict flight delays, which was done in both quantitative (delay for how many minutes) and qualitative (delay exceeds 15 minutes) options. 5 regression and 5 classification models of three different types were built to predict departure delays at the Atlanta airport, USA. …”
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Classification and Comparison of Eight Different Growth Curve Methods for Pekin Duck by Hasan Önder, Mine Yılmaz, Mustafa Şahin, Uğur Şen, Sibel Bozkurt, Kadir Erensoy, İsmail Gök, Tolga Tolun, Ahmet Uçar

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Selection of geometrical features of nuclei оn fluorescent images of cancer cells by Ya. U. Lisitsa, M. M. Yatskou, V. V. Skakun, P. D. Pavel D. Kryvasheyeu, V. V. Apanasovich

“…The use of 11 features is sufficient for the accuracy of classification as it allows to reduce time costs in 2,3 times.…”
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Evaluating Machine Learning Algorithms for Financial Fraud Detection: Insights from Indonesia by Cheng-Wen Lee, Mao-Wen Fu, Chin-Chuan Wang, Muh. Irfandy Azis

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New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model by Mustafa Ismaeel Naif Alheety

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