Statistics on the work of gastroenterologists in the Russian Federation in 2013–2017 by N. E. Guryanova, O. I. Sachek, M. A. Ivanova

“…In recent decades, increasing importance in modern diagnostic algorithms is given to techniques that use optical systems, including those with the ability to examine organs in various spectral ranges and in fluorescence modes. …”
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Psychogenic overeating: problems of classification, diagnosis, approaches to psychotherapy (literature review) by T. A. Karavaeva, M. V. Fomicheva

“…In the article, we analyze the diagnosis of psychogenic overeating (ICD-10), consider the problem of its diagnostic criteria, similarities and differences with the diagnosis of binge-eating disorder (DSM-V), which complicate the work of researchers. …”
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Open-Switch Fault Diagnosis for Grid-Tied HANPC Converters Using Generalized Voltage Residuals Model and Current Polarity in Flexible Distribution Networks by Xing Peng, Fan Xiao, Ming Li, Yizhe Chen, Yifan Gao, Ruifeng Zhao, Jiangang Lu

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ADVANCEMENTS IN TRANSFER LEARNING: A COMPREHENSIVE REVIEW OF NOVEL APPROACHES FOR MRI BRAIN IMAGE DIAGNOSIS by Diyar Waysi, Berivan Tahir Ahmed, Hajar Maseeh Yasin

“…Current research indicates potential challenges in adapting existing supervised deep learning algorithms that process MRI images to more efficient approaches. …”
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Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…A model for the identification of breast cancer based on the lightweight gradient boosting machine (GBM) algorithm. To address the problem of skewed diagnostic data for breast cancer, the Borderline-SMOTE method is used. …”
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Enhancing retinal disease diagnosis through AI: Evaluating performance, ethical considerations, and clinical implementation by Maryam Fatima, Praveen Pachauri, Wasim Akram, Mohd Parvez, Shadab Ahmad, Zeinebou Yahya

“…Background: The research problem addresses the need for accurate and efficient detection of retina diseases using artificial intelligence (AI) technologies. …”
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Bag of Feature-Based Ensemble Subspace KNN Classifier in Muscle Ultrasound Diagnosis of Diabetic Peripheral Neuropathy by Kadhim K. Al-Barazanchi, Ali H. Al-Timemy, Zahid M. Kadhim

“…This work develops a computer-aided diagnostic (CAD) system based on muscle ultrasound that integrates the bag of features (BOF) and an ensemble subspace k-nearest neighbor (KNN) algorithm for DPN detection. …”
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HARDWARE AND SOFTWARE COMPLEX FOR FUNCTIONAL STATE MONITORING OF MOTHER AND FETUS by I. V. Tolmachyov, K. S. Brazovsky, A. S. Tsverova, V. S. Ripenko

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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

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Evaluating axillary lymph node metastasis risks in breast cancer patients via Semi-ALNP: a multicenter studyResearch in context by Limeng Qu, Jinfeng Zhu, Xilong Mei, Zixi Yi, Na Luo, Songlin Yuan, Xuan Liu, Mingwen Liu, Haiqing Xie, Xiongqiang Hu, Liangrui Pan, Qingchun Liang, Yanhui Li, Qiongyan Zou, Qin Zhou, Danhua Zhang, Meirong Zhou, Lei Pei, Ke Qian, Qian Long, Qitong Chen, Xi Chen, Jennifer K. Plichta, Qingyao Shang, Meishuo Ouyang, Jiachi Xu, Wenjun Yi

“…Interpretation: Semi-ALNP, which is based on the MLP algorithm, has high accuracy in assessing the statuses of ALNs across all types of BC patients. …”
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Intelligent diagnosis and prediction of pregnancy induced hypertension in obstetrics and gynecology teaching by integrating GA by Xiaolan Li, Xiaolan Li, Xiaolan Li, Fen Kang, Fen Kang, Fen Kang, Xiaojing Li, Xiaojing Li, Xiaojing Li

“…The potential for misdiagnosis, often stemming from the inexperience of healthcare professionals, underscores the necessity for an advanced diagnostic system.MethodsThis research introduces an innovative sampling and feature selection technique grounded in F-scores optimization, alongside the development of a comprehensive prediction model that integrates genetic algorithms with various heterogeneous learners. …”
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Advanced pathological subtype classification of thyroid cancer using efficientNetB0 by Hongpeng Guo, Junjie Zhang, You Li, Xinghe Pan, Chenglin Sun

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Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

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Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models by Seoyun Choi, Youngmi Lee, Minwoo Lee, Jung Hee Byon, Eun Jung Choi

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ASPECTS OF PULMONARY TUBERCULOSIS VERIFICATION IN THOSE AT THE TERMINAL STAGE OF CHRONIC KIDNEY DISEASE by O. M. Gordeevа, N. L. Kаrpinа, E. E. Lаrionovа, I. Yu. Аndrievskаya, E. A. Kiselevа, O. V. Lovаchevа

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Identification of PRKCQ-AS1 as a Keratinocyte-Derived Exosomal lncRNA That Promotes Th17 Differentiation and IL-17 secretion in Psoriasis Through Bioinformatics, Machine L... by Gao P, Gao X, Lin L, Zhang M, Luo D, Chen C, Li Y, He Y, Liu X, Shi C, Yang R

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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Endoscopic ultrasound (EUS) and Contrast-Enhanced Computed Tomography (CE-CT) were the main diagnostic methods. Non-imaging diagnostic methods such as deep learning urine markers, disease trajectory also performed good diagnostic potential.ConclusionsArtificial intelligence (AI) technology holds promise for clinical guidance in pancreatic cancer risk prediction and diagnosis. …”
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Machine Learning Predictive Models for Survival in Patients with Brain Stroke by Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi

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Development and validation of mRNA expression-based classifiers to predict low-risk thyroid tumors by Allan Golding, David Bimston, Emma Namiranian, Ellen Marqusee, Gabriel Correa, Evana Valenzuela Scheker, Ruochen Jiang, Yangyang Hao, Mohammed Alshalalfa, Jing Huang, Joshua P. Klopper, Richard T. Kloos, Sara Ahmadi

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