Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry by Roxana Pintican, Radu Fechete, Delia Ioana Radutiu, Manuela Lenghel, Ioana Bene, Carolina Solomon, Cristiana Ciortea, Anca Ciurea

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A new stage for predicting the prognosis of granulomatous lobular mastitis. by Ruiyang Wu, Haiyan Zhang, Yan Wang, Yunlu Mo, Huihua Hu, Jin Chen, Wei Huang, Qinyan Shi, Yuqing Kang, Jing Luo

“…<h4>Objective</h4>The purpose of this cohort study was to establish a staging system for GLM to more accurately evaluate the prognosis of patients.<h4>Methods</h4>This study retrospectively collected data from 264 GLM patients who visited our hospital between January 2017 and December 2023. …”
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The Role of Artificial Intelligence in Predicting the Progression of Intraocular Hypertension to Glaucoma by Nicoleta Anton, Cătălin Lisa, Bogdan Doroftei, Ruxandra Angela Pîrvulescu, Ramona Ileana Barac, Ionuț Iulian Lungu, Camelia Margareta Bogdănici

“…Methods: This study involved two groups of patients with IOH and a control group, analyzed using the commercial Neurosolution simulator. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…The efficacy of each algorithm is visually represented through graphical methods and quantitatively evaluated using performance metrics. …”
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Development and validation of a nomogram to predict intracranial haemorrhage in neonates by Shuming Xu, Siqi Zhang, Qing Hou, Lijuan Wei, Biao Wang, Juan Bai, Hanzhou Guan, Yong Zhang, Zhiqiang Li

“…Background: The aim of this study was to establish and validate a Susceptibility-weighted imaging (SWI)-based predictive model for neonatal intracranial haemorrhage (ICH). …”
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An oxidative stress related gene signature predicts prognosis in cholangiocarcinoma by Han Fan, Peng Qiu, Yun Lu, Zhengdong Deng, Li Tian

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Differential gender bias in self-predicted performance in medical tests by Adrian Soto-Mota, Andrés Castañeda Prado, María Fernanda González Lara, Laura Jael Ortiz, Pablo Soto-Mota

“…As part of our sensitivity analyses, we examined whether the perceived difficulty of the evaluated topic or its relevance to their future career plans affected their predictions and test performance. …”
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Defect Prediction in CWDM Optical Modules Using Multimodal Learning by Kyu-Jeong Choi, Jia Yang, Botambu Collins, Sung-Geun Kim, Do-Jin Lim, Jin-Taek Seong

“…The model was comprehensively evaluated on a real CWDM module dataset through cross-validation, based on performance metrics such as accuracy and F1-score. …”
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Risk prediction models for diabetic retinopathy: a systematic review by Hui Huang, Yingmin Wu, Hejiang Ye, Jiaoyang Li, Ling Chen, Xuan Huang

“…BackgroundDiabetic retinopathy, a prevalent complication of diabetes mellitus, is a growing public health concern. The use of robust predictive models can aid healthcare professionals in identifying high-risk patients, enabling them to implement early intervention and treatment strategies.ObjectiveTo systematically evaluate published prediction models for diabetic retinopathy, select better prediction models for healthcare professionals, and provide a valuable reference for model optimization.MethodsA comprehensive search was conducted across the PubMed, Web of Science, Embase, and the Cochrane Library databases for relevant literature on predictive models for diabetic retinopathy. …”
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Prediction of post-contrast acute kidney injury by bedside ultrasonography by Mümin Murat Yazici, Enes Hamdioğlu, Nurullah Parça, Gürkan Altuntaş, Özcan Yavaşi, Özlem Bilir

“…Accordingly, we aimed to evaluate the usefulness of Doppler ultrasound measurements for predicting CI-AKI in patients with normal renal function. …”
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Predicting renal function using fundus photography: role of confounders by Hyun-Woong Park, Hae Ri Kim, Ki Yup Nam, Bum Jun Kim, Taeseen Kang

“…We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. …”
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Physics-Informed Graph Neural Networks for Attack Path Prediction by Marin François, Pierre-Emmanuel Arduin, Myriam Merad

“…However, existing methods become impractical when applied to complex infrastructures. …”
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Blood-Based Prognostic Prediction Model for Glioblastoma: Construction and Validation by Gao S, Liu Y, Kong J, Huangfu L, Yang Y, Cui H, Sun X, Shi S, Yang D

“…Shibo Gao,&ast; Yukun Liu,&ast; Jinglin Kong, Linkuan Huangfu, Yuchuan Yang, Haiyang Cui, Xiaocong Sun, Shuling Shi, Daoke Yang Department of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Daoke Yang, Department of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Henan, People’s Republic of China, Email 15903650068@163.comObjective: Objective: To explore the prognostic factors affecting patients with glioblastoma (GBM) treated with the Stupp regimen and establish a prediction model based on hematological indicators to guide future clinical decision - making.Methods: A total of 271 GBM patients meeting the screening criteria were recruited. …”
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Generalized Additive Model for Predicting ECBR of Stabilized Subgrades for Pavement by Alka Shah, Tejaskumar Thaker, Vipin Shukla

“…Univariate and bivariate GAM were explored to evaluate the influence of parameter interactions on ECBR predictions. …”
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Prediction of early recurrence of pancreatic ductal adenocarcinoma after resection. by Toshitaka Sugawara, Daisuke Ban, Jo Nishino, Shuichi Watanabe, Aya Maekawa, Yoshiya Ishikawa, Keiichi Akahoshi, Kosuke Ogawa, Hiroaki Ono, Atsushi Kudo, Shinji Tanaka, Minoru Tanabe

“…We employed Elastic Net, a sparse modeling method, to construct models predicting early recurrence using these multiple preoperative factors. …”
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Development of an Injury Burden Prediction Model in Professional Baseball Pitchers by Garrett Bullock, Charles Thigpen, Gary Collins, Nigel Arden, Thomas Noonan, Michael Kissenberth, Ellen Shanley

“…A model to predict arm injury burden was produced using zero inflated negative binomial regression. …”
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Factors Predicting CT Pulmonary Angiography Results in the Emergency Department by Nika Rakuša, Zrinka Sertić, Maja Prutki, Ana Marija Alduk, Ivan Gornik

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Deep Learning Models for Predicting the Recurrence of Idiopathic Granulomatous Mastitis by Li L, Yang W, Jia H

“…This study aims to evaluate and compare the performance of different machine learning models, including logistic regression, random forest, and neural networks, in predicting IGM recurrence using patient data.Methods: A retrospective analysis was conducted on 212 patients diagnosed with IGM. …”
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Machine learning models for predicting tibial intramedullary nail length by Sercan Capkin, Ali Ihsan Kilic, Hakan Cici, Mehmet Akdemir, Mert Kahraman Marasli

“…This study employs anthropometric measurements to evaluate and contrast the efficacy of machine learning (ML) models in predicting tibial IMN length. …”
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Application Value of STOP-Bang Questionnaire in Predicting Abnormal Metabolites by Pang Q, Han L, Li J, Xu L, Wang Y

“…Qingyi Pang,1 Li Han,1 Jun Li,2 Lingling Xu,1 Yueheng Wang3 1Department of Endocrinology, Peking Union Medical College Hospital, Beijing, People’s Republic of China; 2Department of Endocrinology, Beijing Hepingli Hospital, Beijing, People’s Republic of China; 3Department of Ear, Nose and Throat, Beijing Hepingli Hospital, Beijing, People’s Republic of ChinaCorrespondence: Lingling Xu; Yueheng Wang, Email llxush@163.com; 8108374@qq.comObjective: To evaluate the application value of STOP-Bang questionnaire (SBQ) in predicting abnormal metabolites.Methods: Totally 121 patients were included into the study and filled the questionnaires, and their clinical data were collected at the same time. …”
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