AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification—Decoding Lateral Epicondylitis in Forearm Muscles by Mehdi Shirzadi, Mónica Rojas Martínez, Joan Francesc Alonso, Leidy Yanet Serna, Joaquim Chaler, Miguel Angel Mañanas, Hamid Reza Marateb

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EVALUATION OF THE EFFECTIVENESS OF A NONSTEROIDAL ANTI-INFLAMMATORY DRUG (NSAID) SELECTION ALGORITHM BASED ON THE ANALYSIS OF RISK FACTORS FOR DRUG-INDUCED COMPLICATIONS IN REAL CL... by A. E. Karateev, A. M. Lila, M. V. Churyukanov, K. V. Skorobogatykh, A. V. Amelin, D. V. Zakharov, E. A. Trofimov, V. A. Shirokov, T. V. Popova, E. A. Shestel, Z. A. Goncharova, A. I. Kulikov, O. B. Nesmeyanova, M. V. Galikhanova

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APPLICATION OF MATHEMATICAL REGRESSION TO THREE-PHASE ASYNCHRONOUS MOTOR PARAMETERS DETERMINATION by Vladimir Borisovich Vorzhev, Ivan Victorovich Kaliyenko

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Comparison of the STANDARD M10 C. difficile, Xpert C. difficile, and BD MAX Cdiff assays as confirmatory tests in a two-step algorithm for diagnosing Clostridioides difficile infec... by Hyunseul Choi, Minhee Kang, Sun Ae Yun, Hui-Jin Yu, Eunsang Suh, Tae Yeul Kim, Hee Jae Huh, Nam Yong Lee

“…In conclusion, the M10 assay is a reliable diagnostic tool, performing comparably to the Xpert and BD MAX assays when used as confirmatory testing in the two-step algorithm.IMPORTANCEWhile numerous studies have assessed nucleic acid amplification tests (NAATs) as stand-alone tests for diagnosing Clostridioides difficile infection, limited research has compared their performance as confirmatory tests in a two-step algorithm. …”
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MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS by V. G. Moreva, G. N. Alekseeva, P. F. Kiku, L. I. Gurina, K. M. Sabirova, V. N. Rasskazova

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MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d’Ivoire by Fateneba Kone, Lucie Conrad, Jean T. Coulibaly, Kigbafori D. Silué, Sören L. Becker, Brama Kone, Issa Sy

“…Machine learning (ML) algorithms were employed for distinguishing P. falciparum-positive from P. falciparum-negative samples. …”
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Interdisciplinary care for newborns with cleft lip and palate in a children's multidisciplinary hospital by A. A. Mamedov, Yu. O. Volkov, A. A. Korsunsky, S. A. Parshikova, L. A. Mazurina, L. M. Makarova, Yu. V. Zirkova, G. P. Tukabaev, G. Ma, H. Guo, N. V. Gorlova

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2024 update of the AGIHO guideline on diagnosis and empirical treatment of fever of unknown origin (FUO) in adult neutropenic patients with solid tumours and hematological malignan... by Michael Sandherr, Jannik Stemler, Enrico Schalk, Tessa Hattenhauer, Marcus Hentrich, Bernd Hertenstein, Christian Hohmann, Sibylle C. Mellinghoff, Rebekka Mispelbaum, Christina Rieger, Martin Schmidt-Hieber, Rosanne Sprute, Guenter Weiss, Oliver A. Cornely, Larissa Henze, Cornelia Lass-Floerl, Gernot Beutel, Annika Y. Classen, Noemi F. Freise, Meinolf Karthaus, Philipp Koehler, Robert Krause, Julia Neuhann, Hans Martin Orth, Olaf Penack, Markus Schaich, Karsten Spiekermann, Sebastian Voigt, Florian Weissinger, Elena Busch

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Comparative assessment of line probe assays and targeted next-generation sequencing in drug-resistant tuberculosis diagnosisResearch in context by Giovanna Carpi, Marva Seifert, Andres De la Rossa, Swapna Uplekar, Camilla Rodrigues, Nestani Tukvadze, Shaheed V. Omar, Anita Suresh, Timothy C. Rodwell, Rebecca E. Colman

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Trade-off between cost and performance of earth observation data in olive trees health assessment: Digital crop mapping approach using machine learning algorithms by Yassine Bouslihim, Abdelkrim Bouasria, Aicha Rochdi, El Bachir El Haissen, Dénes Loczy, Zoltan Orban, Ali Salem

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Swedish regional population-based organised prostate cancer testing: why, what and how? by Ola Bratt, Salma Tunå Butt, Charlotte Carlsson, Lisa Jelf-Eneqvist, Olof Gunnarsson, Alma Ihre, Thomas Jiborn, Anna Lantz, Heide Larsson, Helena Strömqvist, Johan Styrke, Nils-Erik Svedberg, Rebecka Arnsrud Godtman

“… Objective: This study aimed to describe the regional, population-based, organised prostate cancer testing (OPT) programmes that are being introduced throughout Sweden: motives, structure, target population, diagnostic algorithm, quality control, outcomes, research, and future perspectives. …”
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Comparative Characteristics of the Results of Evacuation to Healthcare Facilities and Treatment Outcomes of Children Who Applied for First Aid With Acute Abdominal Pains. The Case... by Ekaterina А. Romanova, Leyla S. Namazova-Baranova, Elena Yu. Dyakonova, Aleksey Yu. Romanov, Kazbek S. Mezhidov, Zharadat I. Dohshukaeva

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Prospects of differential diagnosis of focal lesion of pancreas by the microRNA assessment by M. S. Kniazeva, T. M. Shestopalova, L. M. Zabegina, A. V. Shalaev, A. K. Ratnikova, V. A. Kashchenko, S. L. Vorobyev, A. V. Malek

“…Samples of focal pancreatic lesions after histological evaluation were enrolled in the study including chronic pancreatitis (ChP) (n = 23), low-grade pancreatic intraepithelial neoplasia /PanIN‑1/2 (n = 19), high-grade pancreatic intraepithelial neoplasia /PanIN‑3 (n = 8), and invasive pancreatic ductal adenocarcinoma PDAC (n = 26). Workflow of research included the profiling of cancer-associated miRNA in pooled samples, the selection of potential marker miRNAs, the assessment of selected miRNAs expression in total collection of specimens, the identification of differentially expressed miRNAs, and the approbation of new algorithm of data interpretation via ratio of “reciprocal miRNA pair”. …”
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DINAMIC SCREENING OF PRECANCEROUS ESOPHAGUS USING MOLECULAR GENETIC ANALYSIS by V. V. Anishchenko, S. E. Titov, T. L. Poloz, Yu. A. Veryaskina, A. A. Arkhipova, I. V. Bubnov

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The artificial intelligence revolution in gastric cancer management: clinical applications by Runze Li, Jingfan Li, Yuman Wang, Xiaoyu Liu, Weichao Xu, Runxue Sun, Binqing Xue, Xinqian Zhang, Yikun Ai, Yanru Du, Jianming Jiang

“…This article comprehensively reviews the latest research status and application of artificial intelligence algorithms in gastric cancer, covering multiple dimensions such as image recognition, pathological analysis, personalized treatment, and prognosis risk assessment. …”
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Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care h... by Takashi Fujiwara, Yasuyuki Okumura, Hironobu Tokumasu, Takashi Kanemitsu, Kosei Tajima, Akinori Yuri, Masahiro Iwasaku

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Microcomputed tomography as a diagnostic tool for detection of lymph node metastasis in non-small cell lung cancer: A decision-support approach for pathological examination “A pilo... by Ayten Kayı Cangır, Süleyman Gökalp Güneş, Kaan Orhan, Hilal Özakıncı, Yusuf Kahya, Duru Karasoy, Serpil Dizbay Sak

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How we treat polycythemia vera by V. A. Shuvaev, I. S. Martynkevich

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Artificial Intelligence in Paediatric Urology: Transforming Diagnosis and Treatment by Wesam Khan

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Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United Arab Emirates by Amina Abdelqadir Mohamed AlJasmi, Hatem Ghonim, Mohyi Eldin Fahmy, Aswathy Nair, Shamie Kumar, Dennis Robert, Afrah Abdikarim Mohamed, Hany Abdou, Anumeha Srivastava, Bhargava Reddy

“…In the survey, majority (88.2 %) of the radiologists agreed to turnaround time reduction after AI integration, while 82 % suggested that the AI improved their diagnostic accuracy. Discussion: In contrast with the existing studies, this research uses a substantially large data. …”
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