Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot by Ubiracé Fernando Elihimas Júnior, Jamila Pinho Couto, Wallace Pereira, Michel Pompeu Barros de Oliveira Sá, Eduardo Eriko Tenório de França, Filipe Carrilho Aguiar, Diogo Buarque Cordeiro Cabral, Saulo Barbosa Vasconcelos Alencar, Saulo José da Costa Feitosa, Thais Oliveira Claizoni dos Santos, Helen Conceição dos Santos Elihimas, Emilly Pereira Alves, Marcio José de Carvalho Lima, Frederico Castelo Branco Cavalcanti, Paulo Adriano Schwingel

“…The secondary endpoint was to create a robot based on logistic regression capable of predicting the likelihood that elderly recipients will develop worse renal function one year after KT. …”
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Data Mining Models in Prediction of Vancomycin-Intermediate <i>Staphylococcus aureus</i> in Methicillin-Resistant <i>S. aureus</i> (MRSA) Bacteremia Patients in a Clinical Care Setting by Wei-Chuan Chen, Jiun-Ling Wang, Chi-Chuan Chang, Yusen Eason Lin

“…These findings suggest that data mining techniques can effectively predict VISA bacteremia outcomes in clinical settings. …”
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Gastric Cancer Maximum Tumour Diameter Reduction Rate at CT Examination as a Radiological Index for Predicting Histopathological Regression after Neoadjuvant Treatment: A Multicentre GIRCG Study by Maria Antonietta Mazzei, Giulio Bagnacci, Francesco Gentili, Andrea Nigri, Veronica Pelini, Carla Vindigni, Francesco Giuseppe Mazzei, Gian Luca Baiocchi, Frida Pittiani, Paolo Morgagni, Enrico Petrella, Gianni Mura, Beatrice Verdelli, Maria Bencivenga, Simone Giacopuzzi, Daniele Marrelli, Franco Roviello, Luca Volterrani

“…D-max reduction rate in AGC patients may be helpful as a simple and reproducible radiological index in predicting TRG after NAC.…”
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Combining systemic inflammation biomarkers with traditional prognostic factors to predict surgical site infections in elderly hip fracture patients: a risk factor analysis and dynamic nomogram development by Yuhui Guo, Chengsi Li, Haichuan Guo, Peiyuan Wang, Xuebin Zhang

“…Multivariable logistic regression identified independent risk factors for SSI and developed predictive nomograms. Model stability was validated using an external set of patients treated from July 2022 to June 2023. …”
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Nomograms Predicting Survival, Recurrence and Beneficiary Identification of Adjuvant Chemotherapy in Treatment-naïve Patients with Rectal Cancer who Underwent Upfront Curative Resection: A multi-institutional study by Yukihide Kanemitsu, MD, Tomofumi Uotani, MD, Shunsuke Tsukamoto, PhD, Hideki Ueno, PhD, Megumi Ishiguro, PhD, Soichiro Ishihara, PhD, Koji Komori, PhD, Kenichi Sugihara, PhD, Study Group for Nomogram of the Japanese Society for Cancer of the Colon and Rectum

“…To create and validate nomograms predicting overall survival and recurrence in treatment-naïve rectal cancer (RC) patients who underwent upfront surgery. …”
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A predictive risk‐scoring model for survival prognosis of multiple myeloma based on gain/amplification of 1q21: Experience in a tertiary hospital in South‐Western China by Yanqiu Xiong, Shanshan Liang, Wenjiao Tang, Li Zhang, Yuhuan Zheng, Ling Pan, Ting Niu

“…This model, termed the ultra‐high‐risk (UHR) model, demonstrated superior performance in predicting shorter PFS compared to the R‐ISS stage 3 and R2‐ISS stage 4. …”
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Anemia, Hyperglycemia, and Reduced Left Ventricular Ejection Fraction Improve the GRACE Score&rsquo;s Predictability for In-hospital Mortality in Acute Coronary Syndrome; Single-Centre Cross-Sectional Study by Turu' Allo IJ, Pramudyo M, Akbar MR

“…Incorporating anemia, hyperglycemia, and reduced LVEF increased the AUC to 0.862 (95% CI 0.81– 0.91), enhancing predictive accuracy (p = 0.590). Combining these variables yielded an NRI of 0.075 (p = 0.070) and an IDI of 0.035 (p = 0.029).Conclusion: Incorporating anemia, hyperglycemia, and reduced LVEF into the GRACE score improves its predictive capacity for in-hospital mortality in ACS patients. …”
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Accuracy comparison of Elamn and Jordan artificial neural networks for air particular matter concentration (PM 10) prediction using MODIS satellite images, a case study of Ahvaz. by javad sadidi, hani rezayan, Mohammad reza barshan

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Vitamin D Predicts All-Cause and Cardiac Mortality in Females with Suspected Acute Coronary Syndrome: A Comparison with Brain Natriuretic Peptide and High-Sensitivity C-Reactive Protein by Patrycja A. Naesgaard, Ricardo A. León de la Fuente, Stein Tore Nilsen, Leik Woie, Torbjoern Aarsland, Harry Staines, Dennis W. T. Nilsen

“…Accordingly, vitamin D independently predicts mortality in females with suspected ACS.…”
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Quick sequential organ failure assessment score combined with other sepsis-related risk factors to predict in-hospital mortality: Post-hoc analysis of prospective multicenter study data. by Ryo Ueno, Takateru Masubuchi, Atsushi Shiraishi, Satoshi Gando, Toshikazu Abe, Shigeki Kushimoto, Toshihiko Mayumi, Seitaro Fujishima, Akiyoshi Hagiwara, Toru Hifumi, Akira Endo, Takayuki Komatsu, Joji Kotani, Kohji Okamoto, Junichi Sasaki, Yasukazu Shiino, Yutaka Umemura

“…This study aimed to assess the value of quick sequential organ failure assessment (qSOFA) combined with other risk factors in predicting in-hospital mortality in patients presenting to the emergency department with suspected infection. …”
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SLC22A1 rs622342 Polymorphism Predicts Insulin Resistance Improvement in Patients with Type 2 Diabetes Mellitus Treated with Metformin: A Cross-Sectional Study by Kunrong Wu, Xiaoli Li, Yuedong Xu, Xiaoqian Zhang, Ziwan Guan, Shufang Zhang, Yan Li

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Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

Subjects: “…Material properties prediction…”
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Optimization of fatigue life of the seismic vibrator baseplate considering the coupling effect of welding residual stress by Zhen Chen, Qiaomu Wang, Shulong Nie, Shuang Jing, Bo Kong, Nan Luan

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Fecal occult blood affects intestinal microbial community structure in colorectal cancer by Wu Guodong, Wu Yinhang, Wu Xinyue, Shen Hong, Chu Jian, Qu Zhanbo, Han Shuwen

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Autogenous and drying shrinkage properties of precast recycled aggregate concrete by Ningxu Zhang, Qing Yang, Dapeng Li, Yong Yu, Xiaoyu Jiang, Jinjun Xu

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Statistical Inferences to the Parameter and Reliability Characteristics of Gamma-mixed Rayleigh Distribution under Progressively Censored Data with Application by Kousik Maiti, Suchandan Kayal

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Melting curve analyses in the quantitative real-time polymerase chain reaction of methylated/non-methylated DNA toward the detection of oral cancer using gargle fluid by Yusaku Noma, Hayate Sawayama, Kouta Yamashiro, Keitaro Nishi, Haruka Yoshinaga, Ryota Takaoka, Tsuyoshi Sugiura, Tomonori Sasahira, Tomofumi Hamada, Yasuo Suda, Tatsuo Okui

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Impact of land use types on soil microbial community structure and functional structure in Baihualing Village, China by Ruilong Huang, Wei Li, Shouming Qiu, Yuanli Long, Zhuanfei Zeng, Juan Tang, Qiuhan Huang

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Curcumin-enhanced NIR-II-responsive gold nanobipyramids for targeted HSP 90 inhibition by Zhenying Diao, Youcheng Liang, Yong Liu, Dou Zhang, Long Qiu, Jianbo Sun, Qiaoyou Lu, Yanlei Liu, Daxiang Cui, Ting Yin

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COVID-19, FINANCIAL RISK AND THE AIRLINE INDUSTRY by Kasım Kiracı

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