The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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Copper Metabolism-Related Genes as Biomarkers in Colon Adenoma and Cancer by Zhang T, Fu Y

“…Five machine-learning algorithms were employed to identify biomarkers. The degree of immune infiltration was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and the expression profiles of these biomarkers across various cell types were further characterized using single-cell RNA sequencing (scRNA-seq). …”
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Conflict management training for future educators by N. A. Sokolova, N. V. Sivrikova, E. G. Chernikova, T. G. Ptashko, E. M. Harlanova, S. V. Roslyakova

“…Most students (97,6%) learned algorithms to solve typical interpersonal conflicts and began to choose more constructive strategies to solve them. …”
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Estimating vegetation indices and biophysical parameters for Central European temperate forests with Sentinel-1 SAR data and machine learning by Daniel Paluba, Bertrand Le Saux, Francesco Sarti, Přemysl Štych

“…In the comparison of ML models, the traditional ML algorithms, Random Forest Regressor and Extreme Gradient Boosting (XGB) slightly outperformed the Automatic Machine Learning (AutoML) approach, auto-sklearn, for all forest parameters, achieving high accuracies (R2 between 70% and 86%) and low errors (0.055–0.29 of mean absolute error). …”
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An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The results obtained are focused on the construction of analytical algorithms for establishing indistinguishability under the monitoring, modeling, forecasting state-related processes and complex dynamic multiparameter objects.…”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field. …”
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PIC2O-Sim: A physics-inspired causality-aware dynamic convolutional neural operator for ultra-fast photonic device time-domain simulation by Pingchuan Ma, Haoyu Yang, Zhengqi Gao, Duane S. Boning, Jiaqi Gu

“…Optical simulation plays an important role in photonic hardware design flow. The finite-difference time-domain (FDTD) method is widely adopted to solve time-domain Maxwell equations. …”
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Gender and age characteristics and atrial fibrillation during long-term telemonitoring of the ECG by V.M. Bogomaz, I.O. Berdnyk, L.I. Lysa

“…The aim – to evaluate the possibilities of long-term patch monitoring of the electrocardiogram (ECG) to determine gender and age characteristics of the frequency of detection of atrial fibrillation (AF). …”
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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

“…This study aimed to elucidate biological differences related to pTLS density and develop a radiomic classifier for predicting pTLS density in HCC, offering new insights for clinical diagnosis and treatment.Methods Spatial transcriptomics (n=4) and RNA sequencing data (n=952) were used to identify critical regulators of pTLS density and evaluate their prognostic significance in HCC. …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…We also evaluated the predictive power of these linguistic features using machine learning and identified key thematic structures through semantic network analysis. …”
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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through cross-validation. …”
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Surgical thyroid pathology in Crimea and Sevastopol: the way COVID-19 pandemic altered the frequency and structure of diseases by O. R. Khabarov, D. V. Zima, O. F. Bezrukov, E. Yu. Zyablitskaya, E. R. Asanova, P. E. Maksimova

“…Purpose of the study. To evaluate the impact of the COVID-19 pandemic on the structure of surgical thyroid pathology among the population of the Republic of Crimea and Sevastopol City in 2019–2024 through a retrospective data analysis.Patients and methods. …”
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Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement lo... by Qing Huang, Zihao Jiang, Bo Shi, Jiaxu Meng, Li Shu, Fuyong Hu, Jing Mi

“…Five machine learning (ML) algorithms were employed for risk prediction. Data preprocessing included missing value imputation via random forest. …”
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Predicting p53 Status in IDH‐Mutant Gliomas Using MRI‐Based Radiomic Model by Jiamin Li, Zhihong Lan, Xiao Zhang, Xiaoyun Liang, Hanwei Chen, Xiangrong Yu

“…The predictive performance of the models was evaluated using receiver operating characteristic (ROC) curve analysis. …”
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Surgical interventions in velopharyngeal dysfunction: comparative perceptual speech and nasometric outcomes for three techniques by Ryan Instrum, Agnieszka Dzioba, Anne Dworschak-Stokan, Murad Husein

“…Abstract Background The aim of this study was to evaluate speech outcomes following surgical intervention for velopharyngeal dysfunction (VPD). …”
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Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and ther... by Han Yan, Xinyu Ji, Bohan Li

“…Survival analysis, immune infiltration, pathway enrichment, and drug sensitivity were evaluated to validate the model.ResultsThe ICDRS, based on eight key genes (IL32, AHNAK, ANXA5, FN1, GSN, CNN3, FXYD3, CTSS), effectively stratified BLCA patients into high- and low-risk groups with significant differences in overall survival (OS, P < 0.001). …”
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Prognosis and immune landscape of bladder cancer can be predicted using a novel miRNA signature associated with cuproptosis by Zhilei Zhang, Fang Liu, Yongbo Yu, Fei Xie, Tao Zhu

“…Additionally, we developed a nomogram incorporating clinical characteristics and the miRNA signature to further assess its prognostic value. We evaluated the tumor microenvironment (TME) of every patient using immune ESTIMATE, CIBERSORT, and ssGSEA algorithms. …”
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Validation of Automated Respiratory Event Scoring in Type 3 Home Sleep Apnea Testing by Shiroshita N, Obata R, Kawana F, Kato M, Sato A, Ishiwata S, Yatsu S, Matsumoto H, Shitara J, Murata A, Shimizu M, Kato T, Suda S, Tomita Y, Hiki M, Naito R, Kasai T

“…Nanako Shiroshita,1,* Ryoko Obata,1,2,* Fusae Kawana,1 Mitsue Kato,1 Akihiro Sato,3 Sayaki Ishiwata,3 Shoichiro Yatsu,3 Hiroki Matsumoto,3,4 Jun Shitara,3 Azusa Murata,3 Megumi Shimizu,3 Takao Kato,3,4 Shoko Suda,1,3,4 Yasuhiro Tomita,3– 5 Masaru Hiki,3 Ryo Naito,3,4 Takatoshi Kasai1,3,4 1Cardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; 2Philips Japan, Tokyo, Japan; 3Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; 4Sleep and Sleep-Disordered Breathing Center, Juntendo University Hospital, Tokyo, Japan; 5Sleep Center, Toranomon Hospital, Tokyo, Japan*These authors contributed equally to this workCorrespondence: Takatoshi Kasai, Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan, Tel +81-3-3813-3111, Fax +81-3-5689-0627, Email kasai-t@mx6.nisiq.netPurpose: Home sleep apnea tests (HSATs) using polygraphy devices are becoming increasingly important for evaluating obstructive sleep apnea. Alice NightOne, a widely used polygraphy device, includes automatic scoring software; however, more reliable scoring results can be provided by incorporating advanced algorithmic systems like Somnolyzer. …”
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Trust in Artificial Intelligence–Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review by Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, Owais Ahmed Malik

“…Barriers to trust included algorithmic opacity, insufficient training, and ethical challenges, while enabling factors for health care workers’ trust in AI-CDSS tools were transparency, usability, and clinical reliability. …”
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Bioinformatics‑Based Analysis Reveals Diagnostic Biomarkers and Immune Landscape in Atopic Dermatitis by Yang M, Zhang X, Zhou C, Du Y, Zhou M, Zhang W

“…Least Absolute Shrinkage and Selection Operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to screen hub genes. Immune cell infiltration was evaluated using CIBERSORT. …”
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