Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Differential chemoproteomic analysis of RRS-1 candidate molecule and molecules of several nonsteroidal anti-inflammatory drugs by P. A. Galenko-Yaroshevsky, I. Yu. Torshin, A. N. Gromov, O. A. Gromova, K. F. Suzdalev, R. A. Murashko, A. V. Zelenskaya, A. V. Zadorozhniy, T. R. Glechyan, G. V. Simavonyan, E.M. I. Muhammad

“…Chemoproteomic modeling of pharmacological effects of RRS-1 molecule and a number of well-known NSAIDs (diclofenac, nimesulide, ketorolac) on human proteome was carried out on the basis of numerical prediction algorithms over the space of heterogeneous feature descriptions, developed in the topological approach to recognition by Yu.I. …”
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Relationship between stress hyperglycemia ratio and the incidence of atrial fibrillation in patients after coronary artery bypass grafting: a retrospective study based on the MIMIC... by Runjia Liu, Jiatong Li, Jing Zeng, Yuxuan Tao, Dong Chen, Haixia Li

“…Incorporating SHR into post-CABG risk assessment enhances AF prediction, offering a valuable reference for clinical decision-making. …”
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Integrated Bioinformatics and Experimental Validation Reveal Macrophage Polarization-Related Biomarkers for Osteoarthritis Diagnosis by He Q, Liu L, Hu X, Lin L, Song Z, Xia Y, Lin Q, Wei J, Li S

“…Additionally, various analyses, including immune infiltration, gene set enrichment analysis, competing endogenous RNA (ceRNA) construction, and drug prediction, were conducted. Finally, clinical samples were clinically validated through RT-qPCR (OA: Control = 10: 5) and IHC (6: 5) experiments.Results: Three hub genes (MYC, SIK1, and NFIL3) were identified, and the diagnostic model constructed using them demonstrated good diagnostic efficacy in both internal and external datasets (internal AUC = 0.965, external AUC = 0.847). …”
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Development of a Diagnostic Model for Focal Segmental Glomerulosclerosis: Integrating Machine Learning on Activated Pathways and Clinical Validation by Ge Y, Liu X, Shu J, Jiang X, Wu Y

“…We then developed a highly accurate diagnostic model by integrating nine machine learning algorithms into 101 combinations, achieving near-perfect AUC values across training, validation, and external cohorts. …”
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ATP6V0A4 as a novel prognostic biomarker and potential therapeutic target in oral squamous cell carcinoma by Xiaopu Gao, Jiamin Zhou, Yu Qiao, Chuyin Lin, Guanxiong Zhang, Qiuyu Wu, Zhikang Su, Qianji Zhang, Songkai Huang

“…Further, immunotherapy response prediction models and drug sensitivity analysis were utilized to define therapeutic potential. …”
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Genetic variants of the DLK1, KISS1R, MKRN3 genes in girls with precocious puberty by E. A. Sazhenova, O. Yu. Vasilyeva, E. A. Fonova, M. B. Kankanam Pathiranage, A. Yu. Sambyalova, E. E. Khramova, L. V. Rychkova, S. A. Vasilyev, I. N. Lebedev

“…The pathogenicity of identified genetic variants and the functional significance of the protein synthesized by them were analyzed according to recommendations for interpretation of NGS analysis results using online algorithms for pathogenicity prediction (Variant Effect Predictor, Franklin, Varsome, and PolyPhen2). …”
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New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding by Eszter Boros, József Pintér, Roland Molontay, Kristóf Gergely Prószéky, Nóra Vörhendi, Orsolya Anna Simon, Brigitta Teutsch, Dániel Pálinkás, Levente Frim, Edina Tari, Endre Botond Gagyi, Imre Szabó, Roland Hágendorn, Áron Vincze, Ferenc Izbéki, Zsolt Abonyi-Tóth, Andrea Szentesi, Vivien Vass, Péter Hegyi, Bálint Erőss

“…We analyzed the prospective, multicenter Hungarian GIB Registry’s data. The predictive performance of XGBoost and CatBoost machine-learning algorithms with the Glasgow-Blatchford (GBS), pre-endoscopic Rockall and ABC scores were compared. …”
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Preoperative digital 6-minute walk test reveals risk of postoperative pulmonary complications in patients undergoing heart valve surgery: a pilot feasibility study by Lixuan Li, Yuqiang Wang, Zhengbo Zhang, Zeruxin Luo, Wenqing Wang, Jiachen Wang, Xiaoli Liu, Ying Shi, Tian Yuan, Yong Fan, Hong Liang, Yingqiang Guo, Buqing Wang, Jing Wang, Jiaoxue Deng

“…We extracted 94 physiological features across 6MWT phases (baseline, walking, recovery) and clinical variables, developing predictive models using five machine learning algorithms evaluated through rigorous five-fold cross-validation. …”
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Revisiting Southern Gallo-Romance from a complexity theory standpoint: Occitan by Jean Léo Léonard

“…In this paper, the inner structure of the Occitan dialect network is revisited in the light of a range of cumulative (Ward’s method) vs. reductive (Complete linkage, Groupe Average, Weighted Average) hierarchical algorithms provided by Gabmap, an Online dialectometric application for calculating distance/similarities by edit distance (Levenshtein algorithm). …”
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Monitoring of Thoracopulmonary Compliance During High-Frequency Jet Ventilation: Theoretical and Practical Aspects by M. B. Kontorovich, B. D Zislin, A. V. Chistyakov, A. V. Markov

“…The clinical tests of the developed algorithms permitted a new assessment of the physiological essence of thoracopulmonary compliance during HFJV. …”
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A machine learning‐based approach for wait‐time estimation in healthcare facilities with multi‐stage queues by Amjed Al‐Mousa, Hamza Al‐Zubaidi, Mohammad Al‐Dweik

“…The work employs feature engineering and compares several machine learning‐based algorithms to predict patients' waiting times for single‐stage and multi‐stage services. …”
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External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients. by Lukas Higi, Angela Lisibach, Patrick E Beeler, Monika Lutters, Anne-Laure Blanc, Andrea M Burden, Dominik Stämpfli

“…Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. …”
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A private Ethereum blockchain for organ donation and transplantation based on intelligent smart contracts by V. Sitharamulu, G. Sucharitha, Sachi Nandan Mohanty, Shaik Janbhasha, D. Kothandaraman

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IMPROVEMENT OF MEDICAL CARE FOR THE PATIENTS WITH LIPID DISORDERS (CASE OF LIPID CENTER OF THE “DISTRICT CARDIOLOGICAL DISPENSARY “CENTER FOR DIAGNOSTICS AND CARDIOVASCULAR SURGERY... by K. G. Kozhokar, I. A. Urvantseva

“…Taken high prevalence of the pathology in younger patients, we have developed and implemented an algorithm of the young acute coronary syndrome patients follow-up; developed and approved the algorithms of interaction of the in-patient and outpatient parts of specialized care for lipid disorder patients.Conclusion. …”
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Development of Robust CNN Architecture for Grading and Classification of Renal Cell Carcinoma Histology Images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

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A clinical case with Anti-MOG associated demyelinating disease by D. A. Bazhenova, E. I. Zaydullina, A. A. Malkova, N. V. Komissarova

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Refining daily precipitation estimates using machine learning and multi-source data in alpine regions with unevenly distributed gauges by Huajin Lei, Hongyi Li, Hongyu Zhao

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Failure mechanisms of coral aggregate concrete under compression-shear loading: Experimental investigation and mesoscale simulation by Dongpeng Ma, Xiaona Huang, Zhongyu Lu

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Solving the fully fuzzy multi-choice linear programming model by Zahra Arami, Maryam Arabameri, Hassan Mishmast Nehi

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