Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis by Vivianne Landry, Jessica Matschek, Roger Pang, Meghana Munipalle, Kenneth Tan, Jill Boruff, Nicole Y.K. Li-Jessen

“…Breathing and coughing were the most common biomarkers, with artificial neural networks being the most common analysis technique. Future research on audio biomarkers should focus on testing their validity in clinically diverse populations and resolving algorithmic bias. …”
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In-Hospital Stroke in a Multidisciplinary Hospital by S. S. Petrikov, G. R. Ramazanov, S. B. Binnatova, M. V. Tikhomirova

“…In this regard, there is a need to study the prevalence, risk factors, clinical features of in-hospital stroke, as well as the development of diagnostic and therapeutic algorithms in order to improve the efficiency of care for patients with in-hospital stroke.…”
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Early Detection of Oncological Diseases of the Digestive System (Guidelines of the Russian Gastroenterological Association and the Russian Association of Oncologists for Primary Ca... by V. T. Ivashkin, I. V. Mayev, A. D. Kaprin, M. Yu. Agapov, D. N. Andreev, A. S. Vodoleev, M. Yu. Zharkova, M. P. Korolev, Yu. A. Kucheryavyi, T. L. Lapina, M. V. Mayevskaya, A. V. Okhlobystin, Ch. S. Pavlov, A. V. Paraskevova, S. S. Pirogov, E. A. Poluektova, D. E. Rumyantseva, A. S. Trukhmanov, P. V. Tsarkov, A. A. Sheptulin, O. S. Shifrin

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Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to wh... by Akira Ono, Yukihiro Terada, Takuya Kawata, Masakuni Serizawa, Mitsuhiro Isaka, Takanori Kawabata, Toru Imai, Keita Mori, Koji Muramatsu, Isamu Hayashi, Hirotsugu Kenmotsu, Keiichi Ohshima, Kenichi Urakami, Takeshi Nagashima, Masatoshi Kusuhara, Yasuto Akiyama, Takashi Sugino, Yasuhisa Ohde, Ken Yamaguchi, Toshiaki Takahashi

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Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis by Liang Xu, Jing Li, Wei Gong

“…Precision medicine for tumors represents a pivotal focus in contemporary medical research. Nonetheless, the diversity of tumor types and the complexity of their pathogenesis present significant challenges in the diagnostic process. …”
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Therapy and rehabilitation of women with diabetic adhesive capsulitis by Iryna Zharova, Yevhen Orlenko

“…Observations were carried out using specific clinical (content analysis of medical records, review, clinical laboratory research), instrumental methods (bioimpedance diagnostics of body composition, goniometry, radiography) and sociological (visual analogue pain scale VAS, international questionnaire for assessing the quality of life MOS SF-36 (Medical Outcomes Study)) research methods. …”
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Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease by Mingming Wang, Liping Liang, Zibo Tang, Jimin Han, Lele Wu, Le Liu, Le Liu, Ye Chen, Ye Chen

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Preclinical Cognitive Markers of Alzheimer Disease and Early Diagnosis Using Virtual Reality and Artificial Intelligence: Literature Review by María de la Paz Scribano Parada, Fátima González Palau, Sonia Valladares Rodríguez, Mariano Rincon, Maria José Rico Barroeta, Marta García Rodriguez, Yolanda Bueno Aguado, Ana Herrero Blanco, Estela Díaz-López, Margarita Bachiller Mayoral, Raquel Losada Durán

“…By synthesizing recent studies, it aims to advance early diagnostic methods to detect AD before significant symptoms occur. …”
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Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…Seven classification algorithms – logistic regression, random forest (RF), support vector machine (SVM), Gaussian naive Bayes (GNB), gradient boosting (GB), K-nearest neighbors, and decision tree (DT) – were employed. …”
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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

“…The purpose of this research is to offer novel deep-learning algorithms that target the autonomous categorization of six forms of nail disorders by employing images: Blue Finger, Clubbing, Pitting, Onychogryphosis, Acral Lentiginous Melanoma, and Normal Nail or Healthy Nail Appearance. …”
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Validation study of bullous pemphigoid and pemphigus vulgaris recording in routinely collected electronic primary healthcare records in England by Yana Vinogradova, Julia Hippisley-Cox, Sonia Gran, Sinéad M Langan, Monica S M Persson, Karen E Harman, Kim S Thomas

“…We assessed the positive predictive value (PPV) for bullous pemphigoid and pemphigus vulgaris primary care Read codes in the Clinical Practice Research Datalink (CPRD) using linked inpatient data (Hospital Episode Statistics (HES)) as the diagnostic benchmark.Setting Adult participants with bullous pemphigoid or pemphigus vulgaris registered with HES-linked general practices in England between January 1998 and December 2017. …”
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Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities by Sonam Dukda, Manoharan Kumar, Andrew Calcino, Ulf Schmitz, Matt A. Field

“…Despite significant advances in both the quality and quantity of molecular patient data, diagnostic rates remain suboptimal for many inherited diseases. …”
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Ways to Reduce In-Hospital Mortality in Patients with Cardiogenic Shock in Acute Coronary Syndrome by G. V. Artamonova, V. Yu. Kheraskov, E. V. Grigoryev, O. V. Kushch, D. V. Kryuchkov, L. S. Barbarash

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The role of mitochondria-related genes in hepatocellular carcinoma prognosis: construction of prognostic models based on machine learning by Fei Gao, Fei Teng, Yuxiang Wan, Qiaoli Zhang, Jinchang Huang

“…Conclusions This study highlights the prognostic significance of mitochondrial function-related genes in HCC and establishes a framework for developing innovative diagnostic and therapeutic interventions. Future research should prioritize clinical validation of these findings and evaluate the translational potential of the identified drug candidates in HCC.…”
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From gene expression to causal associations: investigating the role of ferroptosis in cataract development by Chen Li, Xian-bing Yuan, Yi-cheng Lu, Zi-yue Song

“…Additionally, potential diagnostic markers were identified by RT-PCR validation. …”
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Implementation of personalized frameworks in computational thinking development: implications for teaching in software engineering by Josué Guevara-Reyes, Mariuxi Vinueza-Morales, Erick Ruano-Lara, Cristian Vidal-Silva

“…The development of computational thinking (CT) is crucial in software engineering education, as it enables students to analyze complex problems, design algorithmic solutions, and adapt to an evolving digital landscape. …”
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Radiology AI and sustainability paradox: environmental, economic, and social dimensions by Burak Kocak, Andrea Ponsiglione, Valeria Romeo, Lorenzo Ugga, Merel Huisman, Renato Cuocolo

“…Abstract Artificial intelligence (AI) is transforming radiology by improving diagnostic accuracy, streamlining workflows, and enhancing operational efficiency. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. For this study, articles from 2012 to 2023 were considered; after filtering, 82 articles were chosen for primary research. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

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Automatic Calculation of Average Power in Electroencephalography Signals for Enhanced Detection of Brain Activity and Behavioral Patterns by Nuphar Avital, Nataniel Shulkin, Dror Malka

“…Moreover, it bolsters the reliability of real-time brain activity monitoring, potentially advancing neurological diagnostics and insights into cognitive processes. These findings suggest that the technique holds considerable promise for future applications in brain–computer interfaces and advanced neurological assessments, offering a valuable tool for both clinical practice and research exploration.…”
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