Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database by Zhen-Tian Guo, Kun Tian, Xi-Yuan Xie, Yu-Hang Zhang, De-Bao Fang

“…We aimed to establish an effective machine learning (ML) model for predicting the risk of distant metastasis (DM) in medullary thyroid carcinoma (MTC). …”
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Preoperative prediction of multiple biological characteristics in colorectal cancer using MRI and machine learning by Qiao-yi Huang, Hui-da Zheng, Bin Xiong, Qi-ming Huang, Kai Ye, Shu Lin, Jian-hua Xu

“…In this study, we aimed to construct radiomic models through machine learning to predict the progression of CRC. We collected the clinical, pathological, and magnetic resonance imaging (MRI) data of 136 CRC patients who underwent direct surgical resection. …”
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River water quality monitoring using machine learning with multiple possible in-situ scenarios by Dani Irwan, Saerahany Legori Ibrahim, Sarmad Dashti Latif, Chris Aaron Winston, Ali Najah Ahmed, Mohsen Sherif, Amr H. El-Shafie, Ahmed El-Shafie

Subjects: “…Machine learning…”
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Machine learning-based prediction of the mechanical properties of β titanium shape memory alloys by Naoki Nohira, Taichi Ichisawa, Masaki Tahara, Itsuo Kumazawa, Hideki Hosoda

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Effect of phosphorus fractions on benthic chlorophyll-a: Insight from the machine learning models by Yuting Wang, Sangar Khan, Zongwei Lin, Xinxin Qi, Kamel M. Eltohamy, Collins Oduro, Chao Gao, Paul J. Milham, Naicheng Wu

“…To address this gap, we applied two machine learning algorithms—random forest (RF), and artificial neural networks (ANN) to predict benthic chl-a concentrations by incorporating these specific P fractions as separate variables. …”
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Flexible touch and gesture recognition system for curved surfaces with machine learning for assistive applications by Gitansh Verma, Shrutidhara Sarma, Eugen Koch, Andreas Dietzel

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Machine Learning-Driven Optimization for Solution Space Reduction in the Quadratic Multiple Knapsack Problem by Diego Yanez-Oyarce, Carlos Contreras-Bolton, Fredy Troncoso-Espinosa, Carlos Rey

Subjects: “…Machine learning…”
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Voice pathology detection using machine learning algorithms based on different voice databases by Nurul Mu'azzah Abdul Latiff, Fahad Taha Al-Dhief, Nurul Fariesya Suhaila Md Sazihan, Marina Mat Baki, Nik Noordini Nik Abd. Malik, Musatafa Abbas Abbood Albadr, Ali Hashim Abbas

Subjects: “…Machine learning…”
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Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal by Bo Sun

“…The music classifier and deep belief network machine learning models in shallow logistic regression are established, respectively. …”
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Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases by Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba

Subjects: “…machine learning…”
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Advancements in Predictive Analytics: Machine Learning Approaches to Estimating Length of Stay and Mortality in Sepsis by Houssem Ben Khalfallah, Mariem Jelassi, Jacques Demongeot, Narjès Bellamine Ben Saoud

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A systematic literature review and taxonomy proposition of machine learning techniques in smart manufacturing by Frederico de Oliveira Santos, Ivanete Schneider Hahn

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Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Mustafa Alshwayyat, Tala Abdulsalam Alshwayyat, Siya sawan, Ghaith Heilat, Hanan M. Hammouri, Sara Mheid, Batool Al Shweiat, Hamdah Hanifa

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Integrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning by Huilin Chen, Zhenghui Wang, Jiale Shi, Jinghui Peng

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Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning by Zheng-Meng Zhai, Mohammadamin Moradi, Ying-Cheng Lai

“…Further justification for using the LSTM is provided by our comparing its performance with that of alternative machine-learning architectures such as feedforward neural networks and random forest. …”
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Machine learning method based on enhanced CT to predict perineural invasion of rectal cancer by Jiacheng Shen, Long Jin, Shengnan Yin

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Seismic Vulnerability Assessment of Reinforced Concrete Educational Buildings Using Machine Learning Algorithm by Tapan Kumar, Mohammad Al Amin Siddique, Raquib Ahsan

“…The main objective of this paper is to assess the vulnerability of reinforced concrete (RC) educational buildings in Dhaka city to seismic activity by utilizing machine learning (ML) algorithms. There are three main stages in traditional seismic vulnerability assessment: rapid visual assessment (RVA), preliminary engineering assessment (PEA), and detailed engineering assessment (DEA). …”
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Estimation of Anthocyanins in Apple Leaves Based on Ground Hyperspectral Imaging and Machine Learning Models by Yu Zhang, Mi Zou, Yanjun Li, Qingrui Chang, Xing Chen, Zhiyong Dai, Weihao Yuan

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A machine learning based variable selection algorithm for binary classification of perinatal mortality. by Maryam Sadiq, Ramla Shah

“…The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive re-weighted sampling(CARS) and logistic regression for binary classification. …”
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Prediction of end-point phosphorus content of molten steel in BOF with machine learning models by Kang Y., Ren M.-M., Zhao J.-X., Yang L.-B., Zhang Z.-K., Wang Z., Cao G.

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