Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

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Investigating the risks of late preterm and term neonatal morbidity across clinical subtypes of intrahepatic cholestasis of pregnancy by Wei-Zhen Tang, Wei-Zhen Tang, Yi-Fan Zhao, Lan Wang, Qin-Yu Cai, Qin-Yu Cai, Wei-Ze Xu, Li Wen, Xue-Bing Chen, Ting-He Sheng, Ting-He Sheng, Tian-Qi Fan, Tai-Hang Liu, Rong Li, Shang-Jing Liu

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Deep learning-based prediction of individualized Real-time FSH doses in GnRH agonist long protocols by Na Kong, Yu Xia, Zhilong Wang, Hui Zhang, Liyan Duan, Yingchun Zhu, Chenyang Huang, Guijun Yan, Jie Mei, Wujun Li, Haixiang Sun

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Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment by Weidong Zhang, Chenxi Wu, Peifeng Ni, Sheng Zhang, Hongwei Zhang, Ying Zhu, Wei Hu, Mengyuan Diao

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The interaction between triglyceride-glucose index and visceral adiposity in cardiovascular disease risk: findings from a nationwide Chinese cohort by Yuhao Yang, Shengxi Li, Qiao Ren, Yu Qiu, Mengjia Pan, Guanglei Liu, Rise Zheng, Zhenmei An, Shuangqing Li

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Predictive modeling and interpretative analysis of risks of instability in patients with Myasthenia Gravis requiring intensive care unit admission by Chao-Yang Kuo, Emily Chia-Yu Su, Hsu-Ling Yeh, Jiann-Horng Yeh, Hou-Chang Chiu, Chen-Chih Chung

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Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach by Fetlework Gubena Arage, Zinabu Bekele Tadese, Eliyas Addisu Taye, Tigist Kifle Tsegaw, Tsegasilassie Gebremariam Abate, Eyob Akalewold Alemu

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Development and validation of a nomogram model for prolonged length of stay in spinal fusion patients: a retrospective analysis by Linghong Wu, Xiaozhong Peng, Yao Lu, Cuiping Fu, Liujun She, Guangwei Zhu, Xianglong Zhuo, Wei Hu, Xiangtao Xie

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Neutrophil–Lymphocyte Ratio and KELIM Score as Prognostic Markers in High-Grade Serous Advanced Ovarian Cancer Patients Treated with Neoadjuvant Chemotherapy by Vasilis Theodoulidis, Kalliopi Kissoudi, Kimon Chatzistamatiou, Panagiotis Tzitzis, Dimitris Zouzoulas, Iakovos Theodoulidis, Christos Anthoulakis, Theodoros Moysiadis, Maria Topalidou, Eleni Timotheadou, Grigoris Grimpizis, Dimitris Tsolakidis

“…Clinical outcomes, including PFS and OS were analyzed using Kaplan–Meier survival curves, log-rank tests, and Cox regression models. <b>Results</b>: Results demonstrated that elevated NLR (≥3) and low KELIM (<1) were associated with poorer PFS and OS. …”
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Efficacy of ivabradine in patients with poor heart rate control after beta-blocker use in acute myocardial infarction: a pragmatic randomized controlled trial by Yongbin Li, Ying Ren, Lisong Cheng, Xin Zhou, Wenting Li, Lingli Zhang, Jian Cui, Zhuhua Yao

“…Cox proportional hazards modeling analysis showed that Killip classification [hazards ratio (HR) = 1.953, 95% confidence interval (CI): 1.207–2.698, P = 0.012] and peak NT-proBNP value during hospitalization (HR = 2.096, 95% CI: 1.117–3.075, P = 0.028) were influencing factors of hospitalization for heart failure. …”
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A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective by Dung Nguyen Tien, Huong Thi Thu Bui, Tram Hoang Thi Ngoc, Thuy Thi Pham, Dac Trung Nguyen, Huyen Nguyen Thi Thu, Thi Thu Hang Vu, Thi Lan Anh Luong, Lan Thu Hoang, Ho Cam Tu, Nina Körber, Tanja Bauer, Lam Khanh Ho

“…ObjectiveThis study aims to develop a robust predictive model for mother-to-child transmission (MTCT) of HBV using decision tree algorithms, specifically Iterative Dichotomiser 3 (ID3) and classification and regression trees (CART). …”
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Biochemical recurrence prediction after robot-assited radical prostatectomy (BCR-PRARP) by Tanan Bejrananda, Kiyoshi Takahara, Dutsadee Sowanthip, Tomonari Motonaga, Kota Yagi, Wataru Nakamura, Masanobu Saruta, Takuhisa Nukaya, Masashi Takenaka, Kenji Zennami, Manabu Ichino, Hitomi Sasaki, Makoto Sumitomo, Ryoichi Shiroki

“…Cox proportional hazards regression identified predictive variables for BCR. …”
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Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort studyRes... by Renée A.M. Tuinte, Luuk P.J. Smolenaers, Bram T. Knoop, Konstantin Föhse, Tamar J. van der Aart, Hjalmar R. Bouma, Mihai G. Netea, Katrijn Van Deun, Jaap ten Oever, Jacobien J. Hoogerwerf

“…The best performing ML method was compared with other commonly used suspected infection proxies, including the Sepsis-3 definition, an adapted Adult Sepsis Event (ASE) definition and International Classification of Diseases (ICD) codes. …”
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Clinical pharmacists’ interventions about drug therapy problems and its acceptability by prescribers among pediatric hospitalized patients with infectious diseases in resource-limi... by Tilaye Arega Moges, Samuel Berihun Dagnew, Sisay Sitotaw Anberbr, Getachew Yitayew Tarekegn, Taklo Simeneh Yazie, Getu Tesfaw Addis, Teklie Mengie Ayele, Kidist Hunegn Setargew, Fisseha Nigussie Dagnew

“…Cipolle’s and Strand’s DTP classification methods were used for the identification of DTPs. …”
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Multifactorial Risk Stratification in Patients with Heart Failure, Chronic Kidney Disease, and Atrial Fibrillation: A Comprehensive Analysis by Mihai Sorin Iacob, Nilima Rajpal Kundnani, Abhinav Sharma, Vlad Meche, Paul Ciobotaru, Ovidiu Bedreag, Dorel Sandesc, Simona Ruxanda Dragan, Marius Papurica, Livia Claudia Stanga

“…In-hospital mortality was low (2.3%). <b>Conclusions:</b> Traditional risk scores do not fully capture the complexity of multimorbid patients. …”
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The impacts of landscape structure changes on urban surface temperature and heat islands formation of a growing city in southern Sri Lanka by Dilnu Chanuwan Wijesinghe, Dilnu Chanuwan Wijesinghe, Neel Chaminda Withanage, Neel Chaminda Withanage, Prabuddh Kumar Mishra, Wasana Surandi Frenando, Kamal Abdelrahman, Mohammed S. Fnais

“…Different geospatial techniques including supervised image classification, Urban-Rural Gradient Zone (URGZ) analysis, grid-based analysis, UHI profiles, and regression analysis were used in the study. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…K-means clustering and linear regression algorithms were employed to establish a quantitative correlation curve between ventilation quality and panting behavior, forming a Normal-Alert-Danger ventilation quality (VQ) classification standard. …”
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Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth coh... by Sara Fontanella, Clément Frainay, Clare S Murray, Angela Simpson, Adnan Custovic

“…JDINAC with pairwise interactions provided a good balance between sensitivity (0.84) and specificity (0.87), and outperformed penalised logistic regression with individual sIgE components in predicting asthma, with an area under the curve (AUC) of 0.94, compared with 0.73. …”
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Remnant cholesterol predicts risk of recurrent thrombosis beyond LDL-cholesterol in patients with antiphospholipid syndrome by Bin Cai, Yangzhong Zhou, Xinzhuang Yang, Zhaoqing Wang, Can Huang, Qingqing Xiao, Hui Jiang, Yuan Zhao, Xinping Tian, Qian Wang, Guanqiao Li, Mengtao Li, Xiaofeng Zeng, Jiuliang Zhao

“…Methods A prospective analysis was conducted based on a cohort of APS patients who met the 2006 Sydney revised classification criteria. Thrombotic risks associated with varying levels of RC were evaluated using Kaplan–Meier survival analysis and Cox proportional hazards regression models. …”
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Preoperative clinical model to predict myocardial injury after non-cardiac surgery: a retrospective analysis from the MANAGE cohort in a Spanish hospital by Victoria Gomez, Ekaterine Popova, Javier Zamora, María Gómez-Rojo, David Pestaña, Gerard Urrútia, José Manuel del Rey, Ana Belen Serrano, Eva Ureta, Monica Nuñez, Borja Fernández Félix, Elisa Velasco, Javier Burgos, Alfonso Sanjuanbenito, Juan Manuel Monteagudo, Basilio de la Torre, Ángel Candela-Toha

“…Objectives To determine preoperative factors associated to myocardial injury after non-cardiac surgery (MINS) and to develop a prediction model of MINS.Design Retrospective analysis.Setting Tertiary hospital in Spain.Participants Patients aged ≥45 years undergoing major non-cardiac surgery and with at least two measures of troponin levels within the first 3 days of the postoperative period. All patients were screened for the MANAGE trial.Primary and secondary outcome measures We used multivariable logistic regression analysis to study risk factors associated with MINS and created a score predicting the preoperative risk for MINS and a nomogram to facilitate bed-side use. …”
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