Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…At the same time, the global search capability of the model is augmented via an ant colony optimization algorithm to ascertain the final optimized path. …”
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Development and validation of a biomarker-based prediction model for metastasis in patients with colorectal cancer: Application of machine learning algorithms by Erfan Ayubi, Sajjad Farashi, Leili Tapak, Saeid Afshar

“…Subsequently, the prediction model was developed and internally validated using five machine learning (ML) algorithms including lasso and elastic-net regularized generalized linear model (glmnet), k-nearest neighbors (kNN), support vector machine (SVM) with Radial Basis Function Kernel, random forest (RF), and eXtreme Gradient Boosting (XGBoost). …”
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Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis by Yah Ru Juang, Lina Ang, Wei Jie Seow

“…Abstract Numerous prediction models have been developed to identify high-risk individuals for lung cancer screening, with the aim of improving early detection and survival rates. …”
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A machine learning-based screening model for the early detection of prostate cancer developed using serum microRNA data from a mixed cohort of 8,741 participants by Cong Lai, Zhensheng Hu, Zhuohang Li, Zhikai Wu, Kuiqing Li, Lin Li, Hongze Liu, Juanyi Shi, Yi Zhou, Kewei Xu, Cheng Liu

“…Six machine learning algorithms were employed to develop a screening model for PCa using the training dataset. …”
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The short video platform recommendation mechanism based on the improved neural network algorithm to the mainstream media by Mengruo Qi

“…Therefore, in order to address the data sparsity and high-dimensional feature extraction, this study proposes a novel short video platform recommendation model. The proposed method utilizes the term frequency inverse document frequency algorithm for text mining, and combines error back propagation neural network for learning to explore the potential connection between users and videos. …”
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Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study by Yanfei Chen, Bing Wang, Yankai Shi, Wenhao Qi, Shihua Cao, Bingsheng Wang, Ruihan Xie, Jiani Yao, Xiajing Lou, Chaoqun Dong, Xiaohong Zhu, Danni He

“…The study utilised Random Forest and Extreme Gradient Boosting (XGBoost) algorithms alongside traditional logistic regression for modelling. …”
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Validation of three models (Tolcher, Levine, and Burke) for predicting term cesarean section in Chinese population by Fangcan Sun, Minhong Shen, Bing Han, Youguo Chen, Fangfang Wu

“…A predicted probability for CS was calculated for women in the dataset by the algorithm of each model. The performance of the model was evaluated for discrimination. …”
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CELIAC DISEASE SCREENING IN A LARGE DOWN SYNDROME COHORT: COMPARISON OF DIAGNOSTIC YIELD OF DIFFERENT SEROLOGICAL SCREENING TESTS by Dilek Uludağ Alkaya, Seçil Sözen, Birol Öztürk, Nuray Kepil, Tülay Erkan, Hüseyin Tufan Kutlu, Beyhan Tüysüz

“…This study aimed to estimate the prevalence of CD in DS patients and compare the diagnostic performance of the screening algorithms. Material and Method: A cohort of 1117 DS patients were included. …”
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Credit risk identification of high-risk online lending enterprises based on neural network model by Mao-guang WANG, Zi-jun ZHU

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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

“…The findings show that ML algorithms consistently outperform traditional models due to their capacity to handle large, non-linear datasets and continuously enhance predictive accuracy as new patterns emerge. …”
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Predictive model establishment for forward-head posture disorder in primary-school-aged children based on multiple machine learning algorithms by Hongjun Tao, Yang Wen, Rongfang Yu, Yining Xu, Fangliang Yu

“…Multiple machine learning algorithms are applied to construct distinct risk prediction models, with the most effective model selected through comparative analysis. …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…This study demonstrates that machine learning models—particularly the RF algorithm—hold substantial promise for predicting kinesiophobia in postoperative lung cancer patients. …”
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Glitch(ing)! A refusal and gateway to more caring techno-urban worlds? by Mirjana Mitrović, Maja-Lee Voigt

“…With code connecting to concrete in ‘smart’ cities, oppressive, patriarchal, and binary architectures of the urban have been translated into their algorithmic counterparts, too. This particularly excludes people who do not conform to these inscribed norms. …”
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A diagnostic prediction model for anti-neutrophil cytoplasmic antibody associated vasculitis combined with glomerulonephritis based on machine learning algorithm by Wang Jian-mei, Zhu Ge-li, Cao Chen-lin, Peng Qing-quan

“…<italic>EHHADH</italic>， <italic>CCL2</italic>， <italic>FN1</italic>， <italic>IL1B</italic>， <italic>VAV1</italic>， <italic>CXCR4</italic>， <italic>CCL5</italic>， and <italic>CD44</italic>were core genes in the PPI network. The RF algorithm screened out 15 characteristic genes， and the artificial neural network algorithm calculated the weight of each characteristic gene and successfully constructed a diagnostic model. …”
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A diagnostic prediction model for anti-neutrophil cytoplasmic antibody associated vasculitis combined with glomerulonephritis based on machine learning algorithm by Wang Jian-mei, Zhu Ge-li, Cao Chen-lin, Peng Qing-quan

“…EHHADH， CCL2， FN1， IL1B， VAV1， CXCR4， CCL5， and CD44were core genes in the PPI network. The RF algorithm screened out 15 characteristic genes， and the artificial neural network algorithm calculated the weight of each characteristic gene and successfully constructed a diagnostic model. …”
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Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI by Mélanie Karlsen, Sonia Khier, David Fabre, David Marchionni, Jérôme Azé, Sandra Bringay, Pascal Poncelet, Elisa Calvier

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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…The results and statistical analysis revealed that the proposed GOAOA algorithm as an FS technique outperforms the other FS algorithms employed in this study.…”
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Few-shot hotel industry site selection prediction method based on meta learning algorithms and transportation accessibility by Na Li, Huaishi Wu

“…Then, a transportation accessibility calculation model is constructed using spatial syntax for secondary screening. …”
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Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed‐Cohort Study Based on 16,189 Participants by Cong Lai, Zhensheng Hu, Jintao Hu, Zhuohang Li, Lin Li, Mimi Liu, Zhikai Wu, Yi Zhou, Cheng Liu, Kewei Xu

“…Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. …”
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Machine learning algorithms as early diagnostic tools for prolonged operative time in patients with fluorescent laparoscopic cholecystectomy: a retrospective cohort study by Chu Wang, Chu Wang, JunYe Wen, ZiYi Su, HanXiang Yu

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