Improving Malaria diagnosis through interpretable customized CNNs architectures by Md. Faysal Ahamed, Md Nahiduzzaman, Golam Mahmud, Fariya Bintay Shafi, Mohamed Arselene Ayari, Amith Khandakar, M. Abdullah-Al-Wadud, S. M. Riazul Islam

“…We assessed model interpretability using feature activation maps, Gradient-weighted Class Activation Mapping (Grad-CAM) and SHapley Additive exPlanations (SHAP) visualizations for all three architectures, illustrating why SPCNN outperformed the others. …”
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Identification of GABBR2 as a diagnostic marker and its association with Aβ in Alzheimer's disease by Huijun Li, Yawei Fan, Chan Chen, Yuzhong Xu, Xiong Wang, Wei Liu

“…The overlapped hub genes were further processed using machine learning algorithms, intersected with module gene from protein-protein interaction (PPI) network constructed with DEGs, to yield co-hub genes. …”
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Development of an explainable prediction model for portal vein system thrombosis post-splenectomy in patients with cirrhosis by Caixia Dong, Guodong Li, Rui Zhou, Dou Qu, Duwei Dai, Junxia Zhao, Lingbo An, Xiaojie Song, Jiazhen Zhu, Zong Fang Li

“…The five machine learning algorithms (logistic regression, Gaussian Naive Bayes, decision tree, random forest and AdaBoost) were employed to train the predictive models for assessing risks of PVST, which were validated using five fold cross-validation. …”
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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

“…We utilized the Random Forest (RF), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GauNB) algorithms to develop ML-HT models. The models' predictive performance was evaluated using confusion matrix (including accuracy, precision, recall, and F1 score), and discriminative analysis (area under the receiver-operating-characteristic curve, ROC-AUC) in the original cohort, followed by validation in an independent external cohort. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…In this study, sea bottom type data recorded during national monitoring of commercial fishing vessel operations and fishery surveys in the Greek Seas were used. …”
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System architecture and key technologies of intelligent, safe and efficient mining for rockburst coal seams by Zhigang DENG, Yunpeng LI, Shankun ZHAO, Yin WANG, Shaogang LI, Linghai KONG, Junjun JIANG, Zhenguo SU, Yizhe LI, Kai QIN

“…First of all, digital twin technology is used to build a fine digital model, deeply detect and analyze the geological structure of the area where the mine is located, accurately measure the characteristics of the regional geostress field and the physical and mechanical properties of coal and rock, and rely on advanced algorithms to carry out engineering distribution of formation change information to achieve “transparency” of geological information. …”
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Prostate cancer and metabolic syndrome: exploring shared signature genes through integrative analysis of bioinformatics and clinical data by Maomao Guo, Sudong Liang, Zhenghui Guan, Jingcheng Mao, Zhibin Xu, Wenchao Zhao, Hao Bian, Jianfeng Zhu, Jiangping Wang, Xin Jin, Yuan Xia

“…Comprehensively bioinformatics analyses, including functional enrichment, LASSO, and random forest algorithms, coupled with receiver operating characteristic (ROC) and precision recall curve (PRC) analyses were conducted. …”
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An overview of the high-resolution global LAnd surface satellite (Hi-GLASS) products suite by Shunlin Liang, Tao He, Jie Cheng, Bo Jiang, Huaan Jin, Ainong Li, Siwei Li, Liangyun Liu, Xiaobang Liu, Han Ma, Dan-Xia Song, Lin Sun, Yunjun Yao, Wenping Yuan, Yufang Zhang, Feng Tian, Leshi Li

“…Although most of the algorithms have already been published in the literature, we have addressed the challenges of operational implementation to produce the suite of products. …”
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Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis by Lijuan Feng, Kaiyong Bai, Limeng He, Hao Wang, Wei Zhang

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”
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Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea by Na Hyeon Yu, Daeun Shin, Ik Hee Ryu, Tae Keun Yoo, Kyungmin Koh

“…Various machine learning algorithms were trained by incorporating all features from the health check-up data in the development set. …”
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Construction and demolition waste material library based on vision systems dataZenodo by Maria Teresa Calcagni, Giovanni Salerno, Gloria Cosoli, Giuseppe Pandarese, Gian Marco Revel

“…In addition, the benefits of this resource for the scientific and industrial community are discussed, including the possibility of using the data to develop/fine-tune artificial intelligence (AI) algorithms capable of optimising sorting and recycling processes by recognition and discrimination among different types of CDW material using the aforementioned sensors. …”
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Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

“…This enhanced technique is characterized by its algorithmic simplicity, a reduced number of control gains, straightforward implementation on embedded platforms, and low computational and hardware cost, making it particularly suitable for real-time control applications. …”
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Identification of SMYD2 as a candidate diagnostic and prognostic biomarker for gastric cancer by Sichao Wang, Chuanxi Zhao, Dongmei Li, Qingzhi Liu, Cuiping Mao, Shanshan Ding, Shujun Zhang, Wenjing Shang

“…The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate model performance. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Transfer learning strategies enhanced performance for both algorithms, and the greatest model achieved mean accuracy, precision, recall, F1-score and AUROC of 0.799, 0.837, 0.756, 0.794 and 0.863 during internal testing, respectively. …”
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Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Mette Sagbakken, Ahmed Ghannam, Fuad H. Abuadas, Joel Somerville, Joel Somerville, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair

“…Learners also reported an increased cognitive load and heightened stress levels when navigating these more complex, AI-driven activities.Clinical decision support and monitoringAI-enabled alert algorithms and wearable sensors enabled nurses to detect subtle signs of patient deterioration and fever significantly earlier than conventional methods, supporting timelier clinical interventions. …”
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Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data by Jiafeng Peng, Hongxing Zhang, Huaize Wang, Ting Jiang, Minglei Gao, Xingfu Ma, Yingzong Xiong, Yingchun Li, Ran Xu, Junchen Zhu

“…First, the biomarkers associated with OP were identified through differential gene expression analysis, machine learning algorithms, expression validation, and receiver operating characteristic (ROC) curve analysis. …”
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Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.ResultsLow STAT3 expression was significantly associated with poorer OS (hazard ratio [HR] = 1.927, p < 0.001). …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…This network performs convolution operations on features at different instances, enabling the model to capture changes over time and identify long-term dependencies between action features. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…As many as 12 machine learning (ML) algorithms, namely, logistic regression (LR), decision tree (DT), random forest (RF), gradient boosting (GB), AdaBoost, XGBoost, Naive Bayes (NB), support vector machine (SVM), light gradient-boosting machine (LightGBM), K-nearest neighbors (KNN), extremely randomized trees (ET), and voting classifier (VC), were performed. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…Introduction The evaluation of mineral reserves is conducted using various methods, which differ in calculation algorithms, accuracy, speed, the state of the mineral, and the characteristics of exploration activities (Madani, 1997; Ahmadi, 2010). …”
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