Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification by Zhan Wang, Zhaokai Zhou, Shuai Yang, Zhengrui Li, Run Shi, Ruizhi Wang, Kui Liu, Xiaojuan Tang, Qi Li

“…Lastly, various machine learning algorithms were applied to identify novel potential targets of BLCA, following which their pro-tumorigenic effects were experimentally verified. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

“…Existing methodologies, including traditional techniques like the Penman–Monteith model, remote sensing approaches utilizing Solar-Induced Fluorescence (SIF), and machine learning algorithms, have demonstrated varying levels of effectiveness in ET estimation. …”
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Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography by Yujie Ma, Maged Ali Al-Aroomi, Yutian Zheng, Wenjie Ren, Peixuan Liu, Qing Wu, Ye Liang, Canhua Jiang

“…This study evaluates the efficacy of deep learning algorithms for detecting and diagnosing dental caries using cone-beam computed tomography (CBCT) with the Mask R-CNN architecture while comparing various hyperparameters to enhance detection. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…The test’s discriminatory performance was assessed by ROC analysis and two-threshold classification algorithms. Results ApoE4 levels ascertained by the e4Quant test exhibited clear genotype-dependent stratification. …”
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Dynamic and interpretable deep learning model for predicting respiratory failure following cardiac surgery by Man Xu, Hao Liu, Anran Dai, Qilian Tan, Xinlong Zhang, Rui Ding, Chen Chen, Jianjun Zou, Yongjun Li, Yanna Si

“…Feature selection was conducted via the Least Absolute Shrinkage and Selection Operator (LASSO) and Boruta algorithms. Five machine learning models, including logistic regression, multilayer perceptron, extreme gradient boosting, categorical boosting, and deep neural network (DNN), were trained using preoperative and intraoperative variables. …”
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Current and Future Trends of the Automotive Industry by Dieter Hermann Schramm

“…More activities are required for robust algorithms and strategies to hand over control back to the driver in complex situations and even vice versa from the driver to the car in cases where the driver is unable to further control his car, e.g. in case of a heart attack.…”
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Screening and Risk Analysis of Atrial Fibrillation After Radiotherapy for Breast Cancer: Protocol for the Cross-Sectional Cohort Study “Watch Your Heart (WATCH)” by Laura Saint-Lary, Baptiste Pinel, Loic Panh, Gaelle Jimenez, Julien Geffrelot, Youlia Kirova, Jeremy Camilleri, David Broggio, Marie-Odile Bernier, Corinne Mandin, Christelle Levy, Serge Boveda, Juliette Thariat, Sophie Jacob

“…The development of deep learning algorithms for autosegmentation analysis of potentially critical substructures for the occurrence of AF, including cardiac chambers, the sinoatrial node, the atrioventricular node, coronary arteries, and pulmonary veins (PVs), will produce dosimetry linked to previous RT treatment for all contoured structures. …”
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PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorder... by Christine Knaevelsrud, Sebastian Burchert, Till Langhammer, Leona Hammelrath, Annette Brose, Manuel Heinrich, Pavle Zagorscak

“…Predictive analyses focus on classification of non-response using basic algorithms (ie, logistic regression and gradient boosting) for straightforward interpretability and advanced methods (LSTM, DSEM) to capture complex temporal and hierarchical patterns. …”
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Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait loci, a... by Guoqing Liu, Xiangwen Lv, Jiahui Qin, Xingqing Long, Miaomiao Zhu, Chuwen Fu, Jian Xie, Peichun He

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. …”
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Exploring Brain Activity in Different Mental Cognitive Workloads by Sahar Oftadeh Balani, Ali Fawzi Al-Hussainy, Alhan Abd Al-Hassan Shalal, Mohammed Ubaid, Zinab Aluquaily, Jaafar Alamoori, Saeid Motevalli

“…After preprocessing to reduce noise and various artifacts and to obtain a clean signal for every subject, functional connectivity and complexity features were calculated from EEGs through the coherence and permutation entropy algorithms, respectively. Then, repeated measures analysis of variance (ANOVA) was conducted to assess the differences in complexity and connectivity measures across various brain regions between the rest and task states. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…Among 6 machine learning algorithms, the adaptive boosting (Adaboost) model demonstrated the best overall predictive performance, with an area under the curve (AUC) of 0.866 (95% CI: 0.808~0.923; accuracy: 0.832, specificity: 0.884) in the training set and of 0.806 (95% CI: 0.630~0.983; accuracy: 0.795, specificity: 0.971) in the validation set. …”
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Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…In order for Apache Spark to be able to do machine learning processes, in this paper an experiment will be conducted that integrates Apache Spark which acts as a large data processing environment and the concept of parallel computing will be combined with H2O libraries specifically for handling data processing using machine learning algorithms . Based on the results of testing Apache Spark in a cloud computing environment, Apache Spark is able to process weather data obtained from the largest weather data archive, namely NCDC data with data sizes up to 6GB. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. …”
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Burden of chronic spontaneous urticaria in Italy through healthcare resource utilization and direct costs: a retrospective analysis of real-world using administrative healthcare da... by Giulia Ronconi, Letizia Dondi, Silvia Calabria, Leonardo Dondi, Irene Dell’Anno, Lucia Casoli, Diletta Valsecchi, Ornella Bonavita, Eustachio Nettis, Nello Martini, Carlo Piccinni

“…Methods From a large Italian administrative healthcare database (˜5.5 million inhabitants/year), in- and outpatients newly diagnosed with CSU from January 1st, 2016, to December 31st, 2021 (index date) were identified through specific algorithms. Drug dispensations, overnight hospitalizations, emergency department (ED) accesses, local outpatient specialist care and direct costs charged to the Italian National Health Service (SSN) were described throughout the first follow-up year. …”
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Multiplex immunophenotyping of human acute myeloid leukemia patients revealed single -cell heterogeneity with special attention on therapy sensitive and therapy resistant subpopula... by Nikolett Gémes, Benedek Rónaszéki, Szabolcs Modok, Zita Borbényi, Imre Földesi, Éva Trucza, Blanka Godza, Zsuzsanna László, Balázs Csernus, László Krenács, Enikő Bagdi, Enikő Szabó, László G. Puskás, László G. Puskás, Valeria Bertagnolo, Gábor J. Szebeni, Gábor J. Szebeni, Gábor J. Szebeni

“…Unsupervised clustering algorithms such as Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) and Flow cytometry data that builds Self-Organizing Maps (FlowSOM) were used to reveal the LAIP. …”
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A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults by Daisu Abe, Motoki Inaji, Takeshi Hase, Eiichi Suehiro, Naoto Shiomi, Hiroshi Yatsushige, Shin Hirota, Shu Hasegawa, Hiroshi Karibe, Akihiro Miyata, Kenya Kawakita, Kohei Haji, Hideo Aihara, Shoji Yokobori, Takeshi Maeda, Takahiro Onuki, Kotaro Oshio, Nobukazu Komoribayashi, Michiyasu Suzuki, Taketoshi Maehara

“…Among several machine learning algorithms, eXtreme Gradient Boosting (XGBoost) demonstrated the highest predictive accuracy in cross-validation, with an AUROC of 0.81 (±0.07) and an AUPRC of 0.33 (±0.08). …”
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Re-resection of brain metastases – outcomes of an institutional cohort study and literature review by David Wasilewski, Zoe Shaked, Annalena Fuchs, Siyer Roohani, Ran Xu, Max Schlaak, Nikolaj Frost, Martin Misch, David Capper, David Kaul, Julia Onken, Peter Vajkoczy, Felix Ehret

“…Further research to improve patient selection and treatment algorithms is warranted.…”
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A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation by Chang Li, Mei He, PeiChi Shi, Lu Yao, XiangZhi Fang, XueFeng Li, QiLan Li, XiaoBo Yang, JiQian Xu, You Shang, You Shang

“…Patients were stratified into subgroups using k-means clustering based on lactylation levels. Machine learning algorithms, integrated with pseudotime trajectory reconstruction, were employed to map the temporal dynamics of lactylation. …”
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Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth develop... by Jiahe Liu, Lang Chen, Yuxin Chen, Jingsong Luo, Kexin Yu, Linlin Fan, Chan Yong, Huiyu He, Simei Liao, Zongyuan Ge, Lihua Jiang, Lihua Jiang

“…Our study aimed to examine the risk factors associated with IA among Chinese children and adolescents and leverage explainable machine learning (ML) algorithms to predict IA status at the time of assessment, based on Young’s Internet Addiction Test.MethodsThe longitudinal data consisting of 8,824 schoolchildren from the Chengdu Positive Child Development (CPCD) survey were analyzed, where 33.3% of participants were identified with IA (Age: 10.97 ± 2.31, Male: 51.73%). …”
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Longitudinal CE-MRI-based Siamese network with machine learning to predict tumor response in HCC after DEB-TACE by Nan Wei, René Michael Mathy, De-Hua Chang, Philipp Mayer, Jakob Liermann, Christoph Springfeld, Michael T Dill, Thomas Longerich, Georg Lurje, Hans-Ulrich Kauczor, Mark O. Wielpütz, Osman Öcal

“…This study aims to develop and validate a predictive model that integrates deep learning and machine learning algorithms on longitudinal contrast-enhanced MRI (CE-MRI) to predict treatment response in HCC patients undergoing DEB-TACE. …”
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