A Predictor-Corrector Method for Solving Equilibrium Problems by Zong-Ke Bao, Ming Huang, Xi-Qiang Xia

“…One step serves to predict the next point; the other helps to correct the new prediction. …”
Get full text

Guidelines for the management of emergencies and critical illness in pediatric and adult patients with sickle cell disease by Armand Mekontso Dessap, Stephane Dauger, Mehdi Khellaf, Maite Agbakou, Sophie Agut, François Angoulvant, Jean-Benoît Arlet, Cécile Aubron, Florent Baudin, Florence Boissier, Nicolas Bounaud, Pierre Catoire, Jérôme Cecchini, Djamila Chaiba, Anthony Chauvin, Richard Chocron, Benedicte Douay, Delphine Douillet, Narcisse Elenga, Olivier Flechelle, Ségolène Gendreau, Sybille Goddet, Jeremy Guenezan, Anoosha Habibi, Claire Heilbronner, Bérengère Koehl, Pierrick Le Borgne, Philippe Le Conte, Annick Legras, Michael Levy, Bernard Maitre, Mathieu Oberlin, Mehdi Oualha, Nicolas Peschanski, France Pirenne, Corinne Pondarre, Jérôme Rambaud, Keyvan Razazi, Geoffroy Rousseau, Aurélie Schirmann, Isabelle Thuret, Ruddy Valentino, Guillaume Voiriot, Barbara Villoing, Marion Grimaud, Sandrine Jean

“…The section on transfusion therapy addressed indications and methods of transfusion, as well as the diagnosis and prediction of delayed hemolytic transfusion reactions. …”
Get full text

Heart failure and atrial fibrillation: updates and perspectives by V. N. Larina, I. K. Skiba, A. S. Skiba, V. G. Larin, E. A. Vartanyan

“…The article discusses modern approaches and features of management, as well as predicting the risk of complications in patients with cardiac arrhythmias, in particular, atrial fibrillation, and the potential of using conservative and interventional treatment methods for heart failure (HF), taking into account updates and achievements in clinical practice. …”
Get full text

Data-Driven Approach for Intelligent Classification of Tunnel Surrounding Rock Using Integrated Fractal and Machine Learning Methods by Junjie Ma, Tianbin Li, Roohollah Shirani Faradonbeh, Mostafa Sharifzadeh, Jianfeng Wang, Yuyang Huang, Chunchi Ma, Feng Peng, Hang Zhang

“…The proposed GBDT-BO model shows promise for predicting surrounding rock quality and guiding dynamic tunnel excavation and support.…”
Get full text

Characterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices by Maurizio Morisio, Emanuela Noris, Chiara Pagliarani, Stefano Pavone, Amedeo Moine, José Doumet, Luca Ardito

“…Three supervised binary classification algorithms were used to build models capable of predicting the status of the tree quadrant, using the VIs as predictors. …”
Get full text

An automated hip fracture detection, classification system on pelvic radiographs and comparison with 35 clinicians by Abdurrahim Yilmaz, Kadir Gem, Mucahit Kalebasi, Rahmetullah Varol, Zuhtu Oner Gencoglan, Yegor Samoylenko, Hakan Koray Tosyali, Guvenir Okcu, Huseyin Uvet

“…This study proposes an automated system that uses convolutional neural networks (CNNs) to detect potential fracture areas and predict fracture conditions, aiming to outperform traditional object detection-based systems. …”
Get full text

Subgrouping suicidal ideations: an ecological momentary assessment study in psychiatric inpatients by Stephanie Homan, Zachary Roman, Anja Ries, Prabhakaran Santhanam, Sofia Michel, Anna-Marie Bertram, Nina Klee, Carlo Berther, Sarina Blaser, Marion Gabi, Philipp Homan, Hanne Scheerer, Michael Colla, Stefan Vetter, Sebastian Olbrich, Erich Seifritz, Isaac Galatzer-Levy, Tobias Kowatsch, Urte Scholz, Birgit Kleim

“…Abstract Background Suicidal ideation (SI) is one of the strongest predictors of suicide attempts, yet reliable prediction models for suicide risk remain scarce. A key challenge is that SI can fluctuate over time, potentially reflecting different subgroups that may offer important insights for suicide risk prediction. …”
Get full text

Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data by Quan Zhou, Lihua Zhang, Nan Xiang, Lele Zhang, Fuqiang Ma, Fengchang Yu, Shenhui Lv, Zhilin Lu, He-Rong Mao

“…FT4, TPOAB and FT3 were validated as the top three features in the Gradient Boosting model.Conclusions This study innovatively developed a predictive model for benign and malignant TNs based on the Gradient Boosting Decision Tree algorithm. …”
Get full text

LYN and CYBB are pivotal immune and inflammatory genes as diagnostic biomarkers in recurrent spontaneous abortion by Zhuna Wu, Qiuya Lin, Zhimei Zhou, Yajing Xie, Li Huang, Liying Sheng, Qirong Shi, Yumin Ke

“…The performance of the predictive model was evaluated using a Nomo plot. We further confirmed the expression levels and diagnostic value of key genes by performing immunohistochemistry (IHC) in clinical tissue samples. …”
Get full text

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning by ShengHui Miao, YiJing Liu, Min Li, Jing Yan

“…Incorporating early ICU baseline variables into an XGBoost algorithm enables effective prediction of high-mortality risk subgroups (AUC > 0.8). …”
Get full text

Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks by Xiaoying Tang, Zhiqiang Li, Lang Zeng, Hongwei Zhou, Xiaoxu Cheng, Zhenjie Yao

“…By incorporating cost-sensitive learning methods, the proposed model focus more on the critical data that determines device characteristics, leading to accurate prediction of key device characteristics under various parameters. …”
Get full text

Identification of neutrophil extracellular trap-related biomarkers in ulcerative colitis based on bioinformatics and machine learning by Jiao Li, Yupei Liu, Zhiyi Sun, Suqi Zeng, Caisong Zheng

“…Gevokizumab, canakinumab and carboxylated glucosamine were predicted as potential therapeutic drugs for UC.ConclusionBy combining three machine learning algorithms and bioinformatics, this research identified three hub genes that could serve as novel targets for the diagnosis and therapy of UC, which may provide valuable insights into the mechanism of NETs in UC and potential related therapies.…”
Get full text

Identification of Plasma Exosomes hsa_circ_0001360 and hsa_circ_0000038 as Key Biomarkers of Coronary Heart Disease by Wan Zhang, Jiasen Cui, Li Li, Ting Zhu, Zhenyu Guo

“…The corresponding miRNAs of the differentially expressed mRNAs, circRNAs, and lncRNAs were predicted via ENCORI and the miRcode database. LncRNAs/circRNAs and mRNAs with the cotargeted miRNAs were selected to construct an interaction network. …”
Get full text

Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network by Xingyu Duan, Xiaojun Ma, Mengqi Zhu, Linan Wang, Dingqi You, Lili Deng, Ningkui Niu

“…Results Following the segmentation of bare back images and the application of computer vision algorithms, the Dual AttentionUNet model achieved an accuracy, precision, and recall rate of over 90% in predicting severe scoliosis. …”
Get full text

A Novel Dynamic Weight Neural Network Ensemble Model by Kewen Li, Wenying Liu, Kang Zhao, Mingwen Shao, Lu Liu

“…The paper proposes a novel dynamic weight neural network ensemble model (DW-NNE). The Bagging algorithm generates certain neural network individuals which then are selected by the K -means clustering algorithm. …”
Get full text

Establishment of a prognostic model based on ER stress-related cell death genes and proposing a novel combination therapy in acute myeloid leukemia by Minghui Wang, Huajian Xian, Xiaoli Xia, Wenjie Zhang, Zixuan Huang, Chaoqun Lu, Yuling Zheng, Yixin Wang, Shufeng Xie, Renyao Pan, YaoYifu Yu, Ruiheng Wang, Huijian Zheng, Guorui Huang, Han Liu

“…Abstract Background Acute myeloid leukemia (AML) is a highly heterogeneous malignancy, presenting significant challenges in accurately predicting patient prognosis. Dysregulation of endoplasmic reticulum (ER) stress and resistance to programmed cell death (PCD) are hallmarks of AML cells. …”
Get full text

Parameter estimation for networked SIR models with stochastic perturbations using JEKF: a study using COVID-19 daily data from Indian states by Prince Achankunju, Saroj Kumar Dash

“…This sophisticated estimation algorithm iteratively predicts and refines the state based on current estimates, combining model predictions with observed data to enhance accuracy, making it effective for estimating critical parameters in dynamic systems. …”
Get full text

How Re-Infections and Newborns Can Impact Visible and Hidden Epidemic Dynamics? by Igor Nesteruk

“…With the use of effective algorithms for parameter identification, the proposed approach can ensure effective predictions of visible and hidden numbers of cases and infectious and removed patients.…”
Get full text

Exploring the Role of Artificial Intelligence in Dental Implantology: A Scholarly Review by Abdulrahman Ahmed Aseri

“…AI-based technologies, such as machine learning algorithms, neural networks, and computer vision, are being increasingly utilized to interpret diagnostic imaging, predict implant outcomes, and customize treatment protocols tailored to individual patient needs. …”
Get full text

Employee loyalty evaluation using machine learning in technology-based small and medium-sized enterprises by Yong Shi, Yuan Wang, Hongkun zuo

“…Through several machine learning models and algorithms to predict employee loyalty, the feasibility of machine learning to predict employee loyalty is proved, and the evaluation of talent in TSMEs is supported by decision analysis. …”
Get full text