Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle by Akinori Hata, Yohei Muraguchi, Minoru Nakatsugawa, Xinan Wang, Jiyeon Song, Noriaki Wada, Takuya Hino, Kota Aoyagi, Masami Kawagishi, Takuo Negishi, Vladimir I. Valtchinov, Mizuki Nishino, Akihiro Koga, Naoki Sugihara, Masahiro Ozaki, Gary M. Hunninghake, Noriyuki Tomiyama, Mark L. Schiebler, Yi Li, David C. Christiani, Hiroto Hatabu

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A FixMatch Framework for Alzheimer’s Disease Classification: Exploring the Trade-Off Between Supervision and Performance by Al Hossain, Umme Hani Konok, MD Tahsin, Raihan Ul Islam, Mohammad Rifat Ahmmad Rashid, Mohammad Shahadat Hossain, Karl Andersson

“…In this work, we explore whether the FixMatch algorithm—a semi-supervised learning approach—can aid in classifying Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) by using the ADNI fMRI dataset of 5,182 images. …”
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Machine learning prediction and explanation of high intraoperative blood pressure variability for noncardiac surgery using preoperative factors by Zheng Zhang, Yi Duan, Zuozhi Li, Zhifeng Gao, Huan Zhang

“…This study utilized a retrospective observational design, employing the eXtreme Gradient Boosting (XGBoost) algorithm to create a predictive model for high IBPV. …”
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Host Circulating Immunometabolism-Associated Biomarkers for Early Diagnosis of Active Tuberculosis: Multi-Omics Screening with Experimental Validation by Yang Z, Dong Y, Shang Y, Li H, Ren W, Li S, Pang Y

“…Correlation analysis between gene expression and immune cell infiltration was performed using the CIBERSORT algorithm. Single-cell RNA-seq analysis was performed to explore the expression of hub genes in the different immune cells.Results: In this study, we first obtained 41 differentially expressed metabolism-related genes in active TB patients compared to HCs through bulk transcriptomic analysis. …”
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A spatio-temporal fusion-based approach for multi-dimensional classification of Parkinson’s disease progression using multi-modal dataset by Vinay Kukreja, Vandana Ahuja, Modafar Ati, Hariharan Shanmugasundaram, Murugaperumal Krishnamoorthy, Rishabh Sharma, Abhishek Bhattacherjee

“…Context: The progressive neurodegenerative disorder Parkinson’s disease (PD) features diverse symptom presentation that progresses at different speeds and demands effective disease classification with precise patient management. …”
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Obfuscation of combination circuits of digital devices from unauthorized access by L. A. Zolotorevich

“…We consider the formation of a common approach to solving problems of control and verification in the design of modern integrated circuits based on the analysis of fault models of structural realizations of digital devices, errors arising in the design process, as well as deliberate distortions during the design and manufacturing stages, i. e. creation and development of taxonomy of possible deviations in the project. The algorithm of logical obfuscation and coding of digital structures based on the use of methods and means of test diagnostics is proposed.…”
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Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis by Ibrahim Mohammadzadeh, Bardia Hajikarimloo, Behnaz Niroomand, Nasira Faizi, Pooya Eini, Mohammad Amin Habibi, Alireza Mohseni, Mohammadmahdi Sabahi, Abdulrahman Albakr, Michael Karsy, Hamid Borghei-Razavi

“…Additionally, LR-based algorithms showed lower specificity, positive likelihood ratio, and diagnostic odds ratios, but the statistical tests did not provide strong evidence for meaningful differences. …”
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ALLERGIC DISEASES AND METABOLIC SYNDROME: SOME ASPECTS OF THE COMBINED COURSE by V.D. Sakevych, V.I. Sakevych, T.A. Trybrat, S.V. Shut

“…The diagnosis is established based on diagnostic criteria ARIA (2008) (Allergic Rhinitis and its Impact on Asthma (ARIA) 2008 Update (in collaboration with the World Health Organization) for diagnostic algorithm adopted in Ukraine and approved by the Ministry of Health of Ukraine. …”
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Identification and validation of aging related genes in osteoarthritis by Jian Du, Jian Du, Tian Zhou, Yanghui Dong, Yunchao Sun, Wei Peng

“…The DEGs were intersected with ARGs to identify differentially expressed aging related genes (DEARGs), which were then subjected to functional enrichment analysis, PPI network analysis, and machine learning algorithms (LASSO and RF) to identify key genes. In addition, a nomogram was constructed based on the key genes to predict OA risk, and its diagnostic value was evaluated using ROC curves. …”
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Serum Lipid Biomarkers for the Diagnosis and Monitoring of Neuromyelitis Optica Spectrum Disorder: Towards Improved Clinical Management by Li R, Wang J, Wang J, Xie W, Song P, Zhang J, Xu Y, Tian D, Wu L, Wang C

“…Subsequently, we validated the candidate biomarkers in the retrospective cohort and developed diagnostic models using a random forest algorithm. The association between these lipid biomarkers and disease activity was further evaluated in longitudinal analysis.Results: Our analysis identified a panel of serum lipid-related biomarkers that demonstrated significant differences between NMOSD patients and controls. …”
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Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2 by I. Govindharaj, D. Santhakumar, K. Pugazharasi, S. Ravichandran, R. Vijaya Prabhu, J. Raja

“…This approach does not only contribute to glaucoma screening but also can also reveal the benefits of the GANs and transfer learning in medical imaging. • A GAN approach to generate high-quality fundus image datasets in an attempt to minimize dataset differences. • Implemented improved Enhanced Level Set Algorithm for Optic Cup segmentation. • Built on top of the pretrained MobileNetV2 to obtain better results of glaucoma classification.…”
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Utilization of fine needle aspiration cytology at Kamuzu central hospital. by Shiraz Khan, George Liomba, Nora E Rosenberg, Christopher Stanley, Cocxilly Kampani, Bal Mukunda Dhungel, Mina C Hosseinipour

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Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

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Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy by Zachary F. Greenberg, Samantha Ali, Andrew Brock, Jinmai Jiang, Thomas D. Schmittgen, Song Han, Steven J. Hughes, Kiley S. Graim, Mei He

“…However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different methods have been found to derive different EV populations carrying different biomolecules, which significantly confound biomarker discovery for developing clinical diagnostics. …”
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Clinical effectiveness of routine first‐trimester combined screening for pre‐eclampsia in Spain with the addition of placental growth factor by Pablo Garcia‐Manau, Erika Bonacina, Berta Serrano, Sara Caamiña, Marta Ricart, Eva Lopez‐Quesada, Àngels Vives, Monica Lopez, Elena Pintado, Anna Maroto, Sara Catalan, Marta Dalmau, Ester Del Barco, Alina Hernandez, Marta Miserachs, Marta San Jose, Mireia Armengol‐Alsina, Elena Carreras, Manel Mendoza

“…First‐trimester screening using an algorithm that combines maternal characteristics, mean arterial blood pressure, uterine artery pulsatility index and biomarkers (pregnancy‐associated plasma protein‐A and placental growth factor) is the method that achieves a greater diagnostic accuracy. …”
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Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice by Yuke Ren, Yuke Ren, Shuangxing Li, Di Zhang, Yongtian Zhao, Yanwei Yang, Guitao Huo, Xiaobing Zhou, Xingchao Geng, Zhi Lin, Zhe Qu

“…In carcinogenicity studies, drug-induced squamous cell carcinoma (SCC) of the mouse stomach represents a diagnostic challenge for toxicopathologists. This study aims to establish a detection model for mouse gastric squamous cell carcinoma (GSCC) using deep learning algorithms, to improve the accuracy and consistency of pathological diagnoses.MethodsA total of 93 cases of drug-induced mouse GSCC and 56 cases of normal mouse stomach tissue from carcinogenicity studies were collected. …”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Multi-omics analysis constructs a novel neuroendocrine prostate cancer classifier and classification system by Junxiao Shen, Luyuan Lu, Zujie Chen, Wei Guo, Shuwen Wang, Ziqiao Liu, Xuke Gong, Yiming Qi, Ruyi Jin, Cheng Zhang

“…This allows us to select different targeted therapeutic strategies for different subtypes of phenotypic pathways. …”
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Simultaneous determination of 7 thiols associated proteins in lymphoma patients’serum and cerebrospinal fluid by UHPLC-HRMS technique by Qingkun Ma, Mei Zhang, Yongshuai Fan, Han Zhao, Kun Wang, Xiaojing Wang, Yanling Mu

“…Furthermore, a novel PCNSL monitoring model was developed based on different those combined with machine learning algorithm. …”
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Shared and Distinctive Inflammation-Related Protein Profiling in Idiopathic Inflammatory Myopathy with/without Anti-MDA5 Autoantibodies by Zhang Y, Hu W, Li T, Pan Z, Sun J, He Y, Guan W, Zhang L, Lian C, Liu S, Zhang P

“…This study aimed to investigate the inflammation-related protein profiling of IIM patients with different MSAs. In addition, the shared and distinctive inflammation-related protein profiling in IIM with/without anti-MDA5 autoantibodies.Methods: Seventy-seven patients with IIM of different MSAs and 53 gender/age matched healthy controls (HCs) were enrolled in this study. …”
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