Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…By building on our work, researchers can develop better algorithms to improve the diagnosis of AFB, reducing the burden on laboratory staff and improving diagnostic speed and accuracy of these medically important organisms.…”
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Distributed Adaptive Optimization for Generalized Linear Multiagent Systems by Shuxin Liu, Haijun Jiang, Liwei Zhang, Xuehui Mei

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The Need for High-Fidelity Robotics Sensor Models by Phillip J. Durst, Christopher Goodin, Burhman Q. Gates, Christopher L. Cummins, Burney McKinley, Jody D. Priddy, Peter Rander, Brett Browning

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Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus by Yulan Lu, Chunhong Liu, Xiaoxia Pang, Xinghong Chen, Chunfang Wang, Huatuo Huang

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Population characteristics of hostility among the population of a medium urban Siberian city: age and sex aspects by M. M. Kayumova, M. Yu. Akimov, V. V. Gafarov

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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…Moreover, the previous research typically used a limited number of non-industrial images for training, creating a significant disparity with the images encountered in actual applications.MethodsTo investigate the potential of deep learning algorithms in identifying the morphological states of tobacco leaves in real industrial scenarios, a comprehensive and large-scale dataset was developed in this study. …”
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Enabling Autonomous Agents for Mobile Wireless Sensor Networks by José-Borja Castillo-Sánchez, José-Manuel Cano-García, Eva González-Parada, Mirgita Frasheri

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Geohazard impact and gas reservoir pressure dynamics in the Zagros Fold-Thrust Belt: An environmental perspective by Mahsa Asghari, Zahra Maleki, Ali Solgi, Mohammad Ali Ganjavian, Pooria Kianoush

“…A novel hybrid model is introduced that integrates geographic information system (GIS) mapping, decision support system (DSS) modeling, and machine learning algorithms. By analyzing a century's worth of seismic data alongside real-time environmental parameters, the model demonstrates a predictive accuracy of 92% using Random Forest algorithms, significantly outperforming traditional methods. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…This study provides a comprehensive overview of the progress made in applying advanced ML algorithms to assess and monitor GDEs. It begins with a systematic literature review following the PRISMA framework, followed by an analysis of temporal and geographic trends in ML applications for GDE research. …”
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The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy by Szandra László, Ádám Nagy, József Dombi, Emőke Adrienn Hompoth, Emese Rudics, Zoltán Szabó, András Dér, András Búzás, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

“…Several types of features are extracted from both datasets. Machine learning algorithms using different feature sets achieved nearly 90-95% for the CS group and 70-85% accuracy for the PSF. …”
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Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach by Diana-Andreea Căuniac, Andreea-Alexandra Cîrnaru, Simona-Vasilica Oprea, Adela Bâra

“…It is oriented toward research involving new methods and models in the IoT domain related to learning algorithms. …”
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Predicting mother and newborn skin-to-skin contact using a machine learning approach by Sanaz Safarzadeh, Nastaran Safavi Ardabili, Mohammadsadegh Vahidi Farashah, Nasibeh Roozbeh, Fatemeh Darsareh

“…Doula support, neonatal weight, gestational age, attending childbirth classes, and maternal age were the critical predictors for SSC based on the top two algorithms with superior performance. Conclusions Although this study found that the ML model performed well in predicting SSC, more research is needed to make a better conclusion about its performance.…”
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Analysis of the Results of a Questionnaire Survey of Doctors and Clinical Psychologists on Somatovegetative Symptoms of Stress by Anna A. Kuzyukova, Natalia A. Levchenko, Larisa A. Marchenkova

“…The high prevalence of stress conditions among the Russian population contributes to the development of a large number of psychosomatic disorders associated with them, which cause frequent referral of these functional conditions to somatic medical institutions, along with the difficulty of timely diagnosis, which keeps the search and development of diagnostic algorithms aimed at their verification relevant. The National Medical Research Center for Rehabilitation and Balneology is working on the creation of a questionnaire “Comprehensive assessment of the physiological symptoms of stress”, in which a preliminary survey of specialists was conducted. …”
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Effectiveness evaluation of the complex medical and psychological method of treating patients with insomnia by A. V. Vasil'eva, T. A. Karavaeva, Yu. P. Kolesova, D. S. Radionov, D. A. Starunskaya, M. V. Fomicheva, S. M. Abdullaeva

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Machine Learning and Multilayer Perceptron-Based Customized Predictive Models for Individual Processes in Food Factories by Byunghyun Lim, Dongju Kim, Woojin Cho, Jae-Hoi Gu

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Machine learning models for predicting the risk of depressive symptoms in Chinese college students by Chengfu Yu, Xiangxuan Kong, Weijie Yu, Xingcan Ni, Jing Chen, Xiaoyan Liao

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Efficient Joint Transmit and Receive Beam Alignment via Sequential CNN LSTM Networks by Takumi Yoshida, Koji Ishibashi, Hiroki Iimori, Paulo Valente Klaine, Szabolcs Malomsoky

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Medication Adherence: does Patient Participation in Randomized Clinical Trials Affect on it? by N. O. Vasyukova, Yu. V. Lukina, N. P. Kutishenko, S. Yu. Martsevich, O. I. Zvonareva

“…Nevertheless, the article discusses the existing doctor-patient interaction model, which strictly regulates the algorithms and technical means to achieve the best medication adherence. …”
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Scientific Laboratory “Moscow Polyclinic”: Experience of Project Implementation by K. Yu. Tarkhov

“…They shared with the participants their experience of planning, their methodology for conducting a study; algorithms for selecting a study topic, and the features of research data publication, including possible sources. …”
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Translation Strategies for Phonographic Deviations: A Psycholinguistic Approach by Олександр Ребрій, Ганна Тащенко

“…The main method of the research is retrospective experimental technique ‘Partial Delayed Report of Problems and their Solution’; other methods employed include algorithmic modeling (for prospected translation strategies and substrategies) and comparative analysis (for control units in the source and target texts). …”
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