Bayesian approach for localizing cardiac sources in Magnetocardiography using Vectorcardiography based total variational priors by Vikas R. Bhat, Karunakar Kotegar, H. Anitha

“…A novel algorithm is implemented that uses Vectocardiography (VCG) signals in the forward problem of MCG. …”
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Current capabilities of thyroid cancer diagnosis (literature review) by E. E. Bober, I, G, Frolova, E. L. Choinzonov, S. A. Velichko, N. Yu. Bystrova, M. R. Mukhamedov

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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study by Juan Xie, Run-wei Ma, Yu-jing Feng, Yuan Qiao, Hong-yan Zhu, Xing-ping Tao, Wen-juan Chen, Cong-yun Liu, Tan Li, Kai Liu, Li-ming Cheng

“…Nevertheless, the current diagnostic methods, including PCR and bacterial culture, are time-consuming and expensive. …”
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SNUH methylation classifier for CNS tumors by Kwanghoon Lee, Jaemin Jeon, Jin Woo Park, Suwan Yu, Jae-Kyung Won, Kwangsoo Kim, Chul-Kee Park, Sung-Hye Park

“…Abstract Background Methylation profiling of central nervous system (CNS) tumors, pioneered by the German Cancer Research Center, has significantly improved diagnostic accuracy. …”
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A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma by Francesco Martino, Gennaro Ilardi, Silvia Varricchio, Daniela Russo, Rosa Maria Di Crescenzo, Stefania Staibano, Francesco Merolla

“…Our research aimed to create a deep-learning model to generate synthetic Ki-67 immunohistochemistry from Haematoxylin and Eosin (H&E) stained images. …”
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Noninvasive Quantification of Nausea Severity in Pediatric Functional Nausea by Nicole D. Muszynski, Suseela Somarajan, Jordan D. Busing, Alexandra C. Russell, Sari A. Acra, Leonard A. Bradshaw

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Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis by Gabriela Riemekasten, Felix Nensa, Hanna Grasshoff, René Hosch, Malte Maria Sieren, Lennart Berkel, Jörg Barkhausen, Roman Kloeckner, Franz Wegner

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Utilizing Multi-omics analysis to elucidate the role of mitochondrial gene defects in Gastric cancer progression. by Jie Chu, Hanying Song, Kemin Fu, Wei Xiao, Jiudong Jiang, Qixin Gan, Bo Deng

“…Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

“…Subsequently, the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) algorithms were adopted to screen key ARGs related to DN. …”
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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

“…Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. …”
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COMPARATIVE ANALYSIS OF THE SEMIOTICS OF DISSEMINATED PULMONARY TUBERCULOSIS AND EXOGENOUS ALLERGIC ALVEOLITIS IN ACCORDANCE WITH THE DATA OF COMPUTED TOMOGRAPHY by R. B. Amansakhedov, I. V. Limarova, A. V. Perfiliev, R. Yu. Abdullaev, A. T. Sigaev, A. E. Ergeshov

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Frontier machine learning techniques for melanoma skin cancer identification and categorization: An in-Depth review by Viomesh Singh, Kavita A. Sultanpure, Harshwardhan Patil

“…In contrast to the conventional biopsy method, which is both laborious and costly, machine learning algorithms offer a viable alternative for early detection, reducing the burden on specialists while concurrently augmenting the diagnostic accuracy of skin lesions. …”
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A method to evaluate the functional state of the human brain after acute in-hospital stroke by K. S. Brazovskii, D. A. Vinokurova, V. A. Strezh, V. Yu. Ussov

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Artificial intelligence-integrated video analysis of vessel area changes and instrument motion for microsurgical skill assessment by Taku Sugiyama, Minghui Tang, Hiroyuki Sugimori, Marin Sakamoto, Miki Fujimura

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Risk Diagnosis Analysis of Ethane Storage Tank Leakage Based on Fault Tree and Fuzzy Bayesian Network by Min Pang, Zheyuan Zhang, Zhaoming Zhou, Qing Li

“…In order to better cope with the uncertainty of leakage, the weakest t-norm algorithm and the similarity aggregation method are introduced for the parameter learning of the fuzzy Bayesian network to achieve an accurate solution of the model. …”
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Title not available by Bouali, Fakhreddine, Fedala, Semchedine, André, Hugo, Felkaoui, Ahmed

“…Over the past decades, intelligent bearing diagnostic methods have become a research hotspot. These methods require the construction of a Feature Vector (FV) generally composed of indicators calculated from time sampled vibration signals. …”
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Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study by Tiansheng Xia, Kaiyu Han

“…The CatBoost model had the best predictive performance (AUC = 0.805), with smoking as the most significant predictor, followed by blood cadmium concentration and gender. Conclusion In this research, the first risk prediction diagnostic model for heavy metal-chronic bronchitis was developed, in which CatBoost model had the best performance, and it provides a referenceable prediction model for the screening of high-risk groups.…”
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Prediction of Urban Rail Transit Train Door Faults Based on FOA-BP Neural Network Model by WEN Kaiyue, QIU Weibin, DING Xianze, OU Hongxiang

“…[Method] Taking the abnormal current signal of URT train door before failure as the research object, a FIR (finite impulse response) filter is designed to filter and dimensionally normalize the collected URT train door current signal data; the FOA (fruit fly optimization algorithm)-BP (back propagation) neural network model is used to train the closed state learning sample data of different doors after dimensional normalization, and output test results; FOA-BP results and output results after BP neural network models training are compared and analyzed. …”
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Cutting guides in mandibular tumor ablation: Are we as accurate as we think? by Omar Suhaym, Loren Moles, Nicholas Callahan

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Best practices in the laboratory diagnosis, prognostication, prediction, and monitoring of Graves’ disease: role of TRAbs by Sanjay Kalra, Shahjada Selim, Dina Shrestha, Noel Somasundaram, Syed Abbas Raza, Manash P. Baruah, Saptarshi Bhattacharya, Sharvil Gadve, Ganapathi Bantwal, Rakesh Sahay

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