Drying kinetic for moisture content prediction of peels Tahiti lemon (Citrus latifolia): Approach by machine learning and optimization - genetic algorithms and nonlinear programming by Maressa O. Camilo, Romero F. Carvalho, Ariany B.S. Costa, Esly F.C. Junior, Andréa O.S. Costa, Robson C. Sousa

“…The application of a versatile approach for modeling and prediction the moisture content of dried peels was evaluated using both empirical and semi-empirical equations (Lewis, Page, Henderson and Pabis, Modified Page, Logarithmic, and Modified Logistic) as well as machine learning models (K-nearest neighbor | KNN, Decision Tree | DT, Artificial Neural Network | ANN and Support Vector Regression | SVR). …”
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A Panel of Three MicroRNA Signatures as a Potential Biomarker for CRC Screening Based on Stages and Functional Prediction Using Bioinformatic Analysis by Syarah Syamimi Mohamed, Azmir Ahmad, Nurul Syakima Ab Mutalib, Tengku Ahmad Damitri Al-Astani Tengku Din, Md Salzihan Md Salleh, Andee Dzulkarnaen Zakaria, Zaidi Zakaria

“…Although miRNAs appear to be promising screening biomarkers, functional prediction analysis is required to shed light on their role in CRC tumorigenesis. …”
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Donor-Specific Anti-Human Leukocyte Antigen Antibodies Predict Prolonged Isolated Thrombocytopenia and Inferior Outcomes of Haploidentical Hematopoietic Stem Cell Transplantation by Xiaosu Zhao, Xiangyu Zhao, Mingrui Huo, Qiaozhen Fan, Xuying Pei, Yu Wang, Xiaohui Zhang, Lanping Xu, Xiaojun Huang, Kaiyan Liu, Yingjun Chang

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Cross-validation of the safe supplement screener (S3) predicting consistent third-party-tested nutritional supplement use in NCAA Division I athletes by Kinta D. Schott, Avaani Bhalla, Emma Armstrong, Ryan G. N. Seltzer, Floris C. Wardenaar

“…Explorative modeling identified two new variables: TPT logo recognition, and having at least one name, image, likeness (NIL) deal that may help to predict TPT supplement use.DiscussionStrong relationships between risk groupings and product use outcomes toward TPT supplement use were identified for the athletes screened. …”
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Refining MR-guided thermal ablation for HCC within the Milan criteria: a decade of clinical outcomes and predictive modeling at a single institution by Fu-Qun Wei, Pei-Shu Huang, Bing Zhang, Rui Guo, Yan Yuan, Jin Chen, Zheng-Yu Lin

“…A nomogram was developed for survival prediction, followed by risk stratification and internal validation. …”
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High Percentage of ADAM-10 Positive Melanoma Cells Correlates with Paucity of Tumor-Infiltrating Lymphocytes but Does Not Predict Prognosis in Cutaneous Melanoma Patients by Piotr Donizy, Marcin Zietek, Marek Leskiewicz, Agnieszka Halon, Rafal Matkowski

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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

“…Results Our ML‐based radiogenomic modeling identified specific imaging features—wavelet, three‐dimensional local binary patterns, and logarithmic sigma of gray‐level variance—as predictive indicators for high (1) vs. low (0) gene expression of pivotal NSCLC‐related genes: SLC35C1, BCL2L1, and MAPK1. …”
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Clinical calculator based on clinicopathological characteristics predicts local recurrence and overall survival following radical resection of stage II-III colorectal cancer by Fei Huang, Ran Wei, Shiwen Mei, Tixian Xiao, Wei Zhao, Zhaoxu Zheng, Qian Liu

“…Calibration plots illustrated excellent agreement between the clinical risk calculator predictions and actual observations for 3- and 5-year LRFS and OS. …”
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Does binge drinking between the age of 18 and 25 years predict alcohol dependence in adulthood? A retrospective case–control study in France by Marie-Pierre Tavolacci, Joel Ladner, Pierre Déchelotte, Quentin Berthon, Damiano Cerasuolo, Alexandre Baguet

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Epidemiology and Control of diabetes - tuberculosis comorbidity in Eswatini: protocol for the prospective study of tuberculosis patients on predictive factors, treatment outcomes and patient management practices by Diederick E Grobbee, Kerstin Klipstein-Grobusch, Kennedy Otwombe, Victor Williams, Alinda Vos

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Predictive value of monocyte-to-high-density lipoprotein-cholesterol ratio (MHR) for poor prognosis after intravenous thrombolytic therapy for acute ischaemic stroke by Yinglei Li, Lingyun Xi, Litao Li

“…Results MHR level was found to predict the prognosis of intravenous thrombolysis patients with acute ischaemic stroke, and it was an effective predictor of poor prognosis at 3 and 6 months after intravenous thrombolysis. …”
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Prediction of Water Consumption in Hospitals Based on a Modified Grey GM (0, 1∣sin) Model of Oscillation Sequence: The Example of Wuhan City by Han Zhou, Jiejun Huang, Yanbin Yuan, Biao Tang

“…The actual quarterly total water consumption data for hospitals in Wuhan City during the period from 2010 to 2012 were used to verify the effectiveness and practicality of this modified grey GM (0, 1∣sin) model in predicting water consumption. In terms of the model’s fitting performance, the mean absolute percentage error (MAPE) of the modified model was 3.77%, indicating a higher prediction accuracy than the traditional grey GM (0, 1∣sin) model of oscillation sequences. …”
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Model for Vaccine Design by Prediction of B-Epitopes of IEDB Given Perturbations in Peptide Sequence, In Vivo Process, Experimental Techniques, and Source or Host Organisms by Humberto González-Díaz, Lázaro G. Pérez-Montoto, Florencio M. Ubeira

“…The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.…”
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Experimental Assessment of Finite Control Set - Model Predictive Control Applied to a Dual-Converter-Based Rectifier With a Floating DC link by Liane M. de Oliveira, Victor F. M. B. Melo, Iaryssa P. Teles, Emerson de L. Soares, Edison R. C. da Silva, Bruna S. Gehrke, Edgard L. L. Fabrício, Gilielson F. da Paz

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Predicting Outcomes in Esophageal Squamous Cell Carcinoma Using scRNA‐Seq and Bulk RNA‐Seq: A Model Development and Validation Study by Jiaqi Zhang, Shunzhe Song, Yuqing Li, Aixia Gong

“…Conclusion Four hub genes (SERP1, CTSC, RAP2B, and SSR4) screened based on glucose metabolism developed a predictive model in ESCC patients. The RS was established as an independent risk factor for predicting prognosis. …”
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Diagnostic Predictive Value of Tryptase, Serum Amyloid A and Lipoprotein-Associated Phospholipase A2 Biomarker Groups for Large Atherosclerotic Cerebral Infarction by Wenhui Jia, Xia Li, Fang Lei, Fengyun Hu, Fenglian Li, Xueying Zhang, Siyu Liu, Feifei Huang, Changxin Li

“…To assess the diagnostic predictive value of a group of biomarkers for large artery atherosclerotic cerebral infarction. …”
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A Circulating Subpopulation of Monocytic Myeloid-Derived Suppressor Cells as an Independent Prognostic/Predictive Factor in Untreated Non-Small Lung Cancer Patients by Eleni-Kyriaki Vetsika, Filippos Koinis, Marianthi Gioulbasani, Despoina Aggouraki, Anna Koutoulaki, Eirini Skalidaki, Dimitris Mavroudis, Vassilis Georgoulias, Athanasios Kotsakis

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Clinical utility and predictive value of cerebrospinal fluid cell-free DNA profiling in non-small cell lung cancer patients with leptomeningeal metastasis by Sheng-Kai Liang, Wei-Yu Liao, Jin-Yuan Shih, Chia-Lin Hsu, Ching-Yao Yang, Shang-Gin Wu, Yen-Ting Lin, Yueh-Feng Wen, Lun-Che Chen, Yen-Fu Chen, Ya-Fang Chen, Yen-Heng Lin, Chong-Jen Yu

“…Our results highlight CSF cfDNA NGS's potential in LM resistance understanding and ITP efficacy prediction. MET CNG positively impacts survival for ITP recipients, whereas the coexistence of EGFR T790M and EGFR-independent resistance mechanisms leads to poor outcomes.…”
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Synthesis, Molecular Docking, MEP and SAR Analysis, ADME-Tox Predictions, and Antimicrobial Evaluation of Novel Mono- and Tetra-Alkylated Pyrazole and Triazole Ligands by Y. Kaddouri, B. Bouchal, F. Abrigach, M. El Kodadi, M. Bellaoui, R. Touzani

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Nomogram for Predicting In-Hospital Mortality in Patients with Acute ST-Elevation Myocardial Infarction Complicated by Cardiogenic Shock after Primary Percutaneous Coronary Intervention by Yudan Wang, Litian Liu, Xinning Li, Yi Dang, Yingxiao Li, Jiaqi Wang, Xiaoyong Qi

“…The aim of this study is to establish a clinical prognostic nomogram for predicting in-hospital mortality after primary PCI in STEMI patients with CS. …”
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