Multiparametric MRI-based radiomics for preoperative prediction of parametrial invasion in early-stage cervical cancer by Chongshuang Yang, Man Li, Xin Yi, Lin Wang, Guangxian Kuang, Chunfang Zhang, Benyong Yao, Zhihong Qin, Tianliang Shi, Qiang Jiang

Get full text

Development of the continuous ambulatory vestibular assessment (CAVA) system to provide an automatic diagnosis for vestibular conditions: protocol for a multicentre, single-arm, no... by Lee Shepstone, Louisa Murdin, Peter Rea, Juliet High, Ian Nunney, John S Phillips, Gregory Howard, Stephen J Cox

“…The first objective is to develop an algorithm that can discriminate between the three dizziness conditions listed above. …”
Get full text

Efficient Deep Learning Models Revolutionize Doctor’s Training for Point-of-Care Ultrasound by Hsin-Hung Chou, Yi-Chung Chang, Wan-Ching Lien, Lung-Chun Lin, Xing-Zheng Lin, Ting-En Hsu, Yueh-Ping Liu, Li Liu, Yen-Ting Chan, Feng-Sen Kuan

Get full text

Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Among the ten models tested, the LightGBM algorithm exhibited superior performance, with an AUC of 0.853 in the test cohort. …”
Get full text

Prevalence and risk factors of sarcopenic dysphagia in elderly hospitalized patients: a retrospective cohort study based on data from a comprehensive geriatric assessment system by Pingfeng He, Yaling Li, Fu Ding, Xintong Liu, Qiumei Lin

“…The datas including patients’ Body Mass Index (BMI), Daily Living Ability (ADL), Frailty Assessment, Mini Nutrition Assessment Scale (MNA), Chinese simplified Oral health Checklist, Charlson Comorbidity Index (CCI), Geriatric Depression Scale (GDS-5), Water Swallow Test (WST), etc.The prevalence rate of Sarcopenic Dysphagia was calculated by diagnostic algorithm. Risk factors were identified by univariate analysis and multivariable analysis. …”
Get full text

MULTIDISCIPLINARY APPROACH TO SUPPORTING TREATMENT COMPLIANCE IN TUBERCULOSIS PATIENTS by T. V. Sherstneva, S. N. Skornyakov, V. A. Podgaeva, S. V. Sherstnev, A. I. Tsvetkov

Get full text

Summary of updates to the 2021 European Society of Cardiology Guidelines for the diagnosis and treatment of acute and chronic heart failure by V. N. Larina, I. K. Skiba, A. S. Skiba

Get full text

Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…This approach enhances the flexibility of algorithms by incorporating diverse data. A growing quantity of current research has focused on the exploration of extracting data from multiple sources and constructing precise multimodal machine/deep learning models for medical examinations. …”
Get full text

A Pilot Study on Mixed-Reality Approaches for Detecting Upper-Limb Dysfunction in Multiple Sclerosis: Insights on Cerebellar Tremor by Etty Sabatino, Miriam Moschetta, Andrea Lucaroni, Giacinto Barresi, Carlo Ferraresi, Jessica Podda, Erica Grange, Giampaolo Brichetto, Anna Bucchieri

Get full text

Medical Imaging Foundation Models: Paradigm Innovation in Precision Oncology by LIU Zaiyi, ZHAO Zhihe, SHI Zhenwei

“…Based on the research background of artificial intelligence (AI) large-scale models, this article systematically reviews the current research status of medical imaging large-scale models from three key dimensions: the construction of large-scale medical imaging datasets, optimization of large-scale model algorithms, and computational resource requirements. …”
Get full text

Modern echocardiographic criteria for heart failure with preserved ejection fraction: not only diastolic dysfunction by O. M. Drapkina, O. N. Dzhioeva

Get full text

Chorioretinal folds as a symptom of orbital neoplasia. A case report by S. N. Svetozarskiy, G. S. Igonin

Get full text

Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

Get full text

Recent Advancements in Neuroimaging‐Based Alzheimer's Disease Prediction Using Deep Learning Approaches in e‐Health: A Systematic Review by Zia‐Ur‐Rehman, Mohd Khalid Awang, Ghulam Ali, Muhammad Faheem

“…Results Current developments show that CNN‐based techniques, especially those utilizing hybrid and transfer learning frameworks, outperform conventional DL methods. Research employing the combination of multimodal neuroimaging data has demonstrated enhanced diagnostic precision. …”
Get full text

Application of Intravoxel Incoherent Motion in the Prediction of Intra-Tumoral Tertiary Lymphoid Structures in Hepatocellular Carcinoma by Ma L, Liao S, Zhang X, Zhou F, Geng Z, Hu J, Zhang Y, Zhang C, Meng T, Wang S, Xie C

“…The logistic regression algorithm was used to construct the prediction model based on the combination of these features. …”
Get full text

Clinical and Epidemiological Manifestations of Ixodic Tick-Borne Borreliosis Foci in the Tomsk region by O. V. Voronkova, E. N. Ilyinskikh, A. A. Rudikov, T. N. Poltoratskaya, I. E. Esimova, L. V. Lukashova, M. R. Karpova

“…The study of the genotypic diversity of pathogenic borrelias in relation to the species diversity of vectors, the analysis of the clinical manifestations of different etiological variants of tick-borne borreliosis (mono- and mixed infections), as well as the development of an algorithm for differential diagnostic search and a model for predicting the outcomes of the infectious process in tick-borne borreliosis and mixed infections are priority directions of problem-oriented scientific research in Tomsk region.…”
Get full text

Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…Furthermore, Noscapine, PX-316, and TAK-901 were selected as potential therapeutic drugs for AD based on PLCB1. This research provides a comprehensive and reliable method for the discovery of AD therapeutic targets and the construction of diagnostic models, offering important insights and directions for future AD treatment strategies and drug development.…”
Get full text

Identification of signature genes and subtypes for heart failure diagnosis based on machine learning by Yanlong Zhang, Yanming Fan, Fei Cheng, Dan Chen, Hualong Zhang

“…Consequently, identifying specific genes for HF at the transcriptomic level may enhance early detection and allow for more targeted therapies for these individuals.MethodsHF datasets were acquired from the Gene Expression Omnibus (GEO) database (GSE57338), and through the application of bioinformatics and machine-learning algorithms. We identified four candidate genes (FCN3, MNS1, SMOC2, and FREM1) that may serve as potential diagnostics for HF. …”
Get full text

Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia by Caitlin A. Finney, David A. Brown, Artur Shvetcov

“…Our results, however, demonstrated that there are limitations when using publicly accessible cohort data that may limit the generalizability and interpretability of such predictive models. Future research should examine the use of routine APOE genetic testing for dementia diagnostics. …”
Get full text

Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…However, challenges include smaller datasets, breed variability, and limited research. Addressing these through focused research on species with less phenotypic variability (like cats) and cross-sector collaborations could advance AI in veterinary medicine. …”
Get full text