Relevant bibliographies by topics / AI Diagnostics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'AI Diagnostics'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "AI Diagnostics"

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Haferlach, Torsten. "AI in Diagnostics." Clinical Lymphoma Myeloma and Leukemia 24 (September 2024): S25—S26. http://dx.doi.org/10.1016/s2152-2650(24)00333-1.

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Hull, Mary Louise. "Can AI Improve Imaging Diagnostics?" Fertility & Reproduction 05, no. 04 (2023): 211. http://dx.doi.org/10.1142/s2661318223740250.

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The 2016 Cochrane Review identified Magnetic Resonance Imaging (MRI) and Transvaginal Ultrasound scans (TVUS) as the most diagnostic non-invasive test for endometriosis. This led to IMAGENDO, which uses Artificial Intelligence (AI) to model digital data from these two imaging modalities to improve the accuracy of endometriosis non-invasive diagnostics. The IMAGENDO team have developed a novel, award winning, multimodal approach to improve the sensitivity and specificity of endometriosis imaging. The talk will describe some of the methods used, the impact AI has had on diagnostic accuracy and t
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Czerwinska, Magdalena, Joanna Ejdys, and Agnieszka Rzepka. "Understanding patient attitudes towards the use of AI in medical diagnosis using Necessary Conditions Analysis." European Conference on Innovation and Entrepreneurship 19, no. 1 (2024): 984–86. http://dx.doi.org/10.34190/ecie.19.1.2864.

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The recent years have brought a rapid growth in the use of artificial intelligence (AI), particularly in medical applications. One of the areas where AI can find application is in medical diagnostics. AI has the potential to revolutionize the field of medical diagnostics by improving the predictive accuracy, speed and efficiency of the diagnostic process. The literature provides many studies on the applications of AI in medical diagnostics, including the attitudes of medical personnel towards this technology. However, few studies focus on evaluating the use of AI in medicine from the perspecti
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Thayil, Jerry John. "AI-Driven Diagnostics: Revolutionizing Healthcare Precision." European Journal of Biology and Medical Science Research 12, no. 3 (2024): 93–99. https://doi.org/10.37745/ejbmsr.2013/vol12n39399.

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Integrating Artificial Intelligence (AI) into healthcare diagnostics has emerged as a transformative force, enhancing precision, efficiency, and patient outcomes. This white paper explores the current challenges faced in traditional diagnostic methodologies, presents AI-driven solutions, and highlights the benefits of these technologies across various healthcare organizations. By harnessing the power of advanced algorithms, healthcare providers can significantly improve diagnostic accuracy, reduce operational inefficiencies, and ultimately transform patient care.
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Ejdys, Joanna, Magdalena Czerwińska, and Romualdas Ginevičius. "Social acceptance of artificial intelligence (AI) application for improving medical service diagnostics." Human Technology 20, no. 1 (2024): 155–77. http://dx.doi.org/10.14254/1795-6889.2024.20-1.8.

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The aim of the conducted research was to assess the attitude of the Polish society towards the use of artificial intelligence in medical diagnostics. In the research process, we sought answers to three research questions: how trust in the use of AI for medical diagnostics can be measured; if societal openness to technology determines trust in the use of AI for medical diagnostics purposes; and if a higher level of trust in the use of AI for medical diagnostics influences the potential improvement in the quality of medical diagnostics as perceived by Poles. The authors' particular focus was on
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Vasilyev, A. O., A. V. Govorov, Yu A. Kim, P. A. Arutyunyan, and D. Yu Pushkar. "Artificial intelligence in early diagnosis of prostate cancer." Experimental and Сlinical Urology 18, no. 1 (2025): 42–49. https://doi.org/10.29188/2222-8543-2025-18-1-42-49.

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Introduction. To assess the prospects of using artificial intelligence (AI) for the diagnosis and treatment of prostate cancer (PCa) and to evaluate the impact of AI on treatment efficacy. Materials and Methods. A systematic literature review was conducted using scientific databases based on key queries related to AI and PCa. Studies from the last 10 years were included. Results. AI algorithms, such as machine learning (ML) and deep learning (DL), improve the quality of PCa diagnostics, minimize subjective factors, and optimize the diagnostic process. The implementation of computer-aided detec
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Emmanuel K., Mugisha. "AI-Powered Diagnostics: Revolutionizing Early Disease Detection." Research Output Journal of Biological and Applied Science 4, no. 3 (2024): 11–14. http://dx.doi.org/10.59298/rojbas/2024/431114.

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Artificial Intelligence (AI) is reshaping the healthcare landscape by enhancing early disease detection and improving diagnostic accuracy. By leveraging machine learning and deep learning techniques, AI can process vast amounts of medical data, identify patterns, and assist clinicians in making faster, more accurate diagnoses. This paper examines the role of AI in medical diagnostics, with a focus on early detection of chronic diseases, such as cancer and cardiovascular conditions, through case studies. It also highlights the challenges, including data privacy concerns, algorithmic bias, and t
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Adeniyi, Michael, Victoria Bukky Ayoola, Temilayo Esther Samuel, and Wuraola Awosan. "Artificial Intelligence-Driven Wearable Electronics and Smart Nanodevices for Continuous Cancer Monitoring and Enhanced Diagnostic Accuracy." International Journal of Scientific Research and Modern Technology (IJSRMT) 3, no. 11 (2024): 3–18. http://dx.doi.org/10.38124/ijsrmt.v3i11.106.

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Artificial Intelligence (AI)-driven wearable electronics and smart nanodevices are transforming cancer diagnostics by offering continuous monitoring and enhanced diagnostic accuracy. Traditional cancer diagnostic methods often suffer from delays in detection and limited real-time data, which can hinder timely treatment. In contrast, AI integration in wearable technologies and nanodevices allows for the continuous tracking of physiological biomarkers, enabling earlier detection of cancer and more precise monitoring of disease progression. This review explores the advancements in AI-powered wear
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Researcher. "HUMAN-AI COLLABORATION IN HEALTHCARE DIAGNOSTICS: ENHANCING ACCURACY AND PATIENT OUTCOMES." International Journal of Computer Engineering and Technology (IJCET) 15, no. 5 (2024): 814–28. https://doi.org/10.5281/zenodo.13918695.

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This comprehensive article explores the rapidly evolving landscape of human-AI collaboration in healthcare diagnostics, focusing on its applications, benefits, and challenges. The integration of AI in healthcare is transforming medical processes, particularly in diagnostics and medical imaging. With the global AI healthcare market projected to reach $187.95 billion by 2030, AI-assisted systems demonstrate remarkable accuracy in detecting various conditions, often matching or surpassing human experts. The article delves into key technologies such as Natural Language Processing, Computer Vision,
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Kailash, Alle. "AI in Healthcare: Predictive Analytics and Diagnostics." Journal of Scientific and Engineering Research 7, no. 9 (2020): 233–37. https://doi.org/10.5281/zenodo.13347491.

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Predictive analytics and decision support systems are changing patient care in artificial intelligence (AI) in healthcare. Through the identification of trends and risk variables, predictive analytics ease early illness prevention and diagnosis, improving patient outcomes and enabling cost-effective healthcare. By using unique patient data to create customized therapies that maximize benefits and reduce side effects, machine learning enables individualized treatment strategies. AI-driven algorithms improve diagnostic precision in medical imaging by delivering quick and correct evaluations. Hea
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Dissertations / Theses on the topic "AI Diagnostics"

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TISATO, Flavia. "Study on Modern and Contemporary works of Art through non invasive integrated physical techniques." Doctoral thesis, Università degli studi di Ferrara, 2014. http://hdl.handle.net/11392/2388948.

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During my PhD I developed two parallel and complementary topics, concerning both works of art and materials. The first one, focused on non-invasive investigations on works of art (ancient and contemporary), was aimed to deepen conservative state, material composition, painting techniques and the early detection of any deterioration. This latter goal also guided the study of pictorial and restoration materials, mainly aimed at their characterization from the optical point of view. Diagnostic activities made use of different methods of investigation. Among image techniques, photography and macr
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Corradetti, Veronica. "Esperienza di tecniche diagnostiche non distruttive ai fini energetici e strutturali." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2590/.

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Larici, Fabrizio. "Prove non distruttive e meccaniche ai fini della diagnostica energetica e strutturale di edifici storici." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2446/.

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Ghezzi, Francesco. "Il restauro del Monumento ai Caduti (1932) di Forlì: rilievo del degrado e indagini diagnostiche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Il lavoro di Tesi si occupa del restauro sul Monumento ai Caduti di Forlì, programmato in seguito ad un intervento di pulitura del bene non del tutto adeguato. Il presente elaborato include molteplici aspetti d'indagine sull'opera: un breve studio sulle problematiche degli interventi sul moderno, un approfondimento storico sulla nascita dell’opera e sulla sua composizione, un accurato rilievo dei materiali e del degrado e, infine, una campagna di indagini diagnostiche. Le considerazioni sul restauro del moderno hanno permesso di sottolineare il valore e l’importanza di un approccio consono a q
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Lan, Zhengyang. "Towards credible diagnostic tools for neurological gait disorders : a fusion of 3D kinematics, deep learning, and explainable AI." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2025. http://www.theses.fr/2025IMTA0476.

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Les anomalies de la marche sont fréquentes chez les enfants et peuvent être provoquées par diverses pathologies. L’analyse du schéma de marche à l’aide de techniques d’analyse 3D fournit des informations cliniques précieuses. Dans cette thèse, nous avons cherché à déterminer si l’apprentissage profond pouvait être intégré aux données d’analyse 3D de la marche afin de diagnostiquer les troubles de la marche chez lesenfants. Nous avons évalué la précision diagnostique de plusieurs méthodes d’apprentissage profond sur six ensembles de données contenant des analyses 3D de la marche, provenant de c
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Cheang, Tak Son. "Math-model based machinery and AI-based diagnostic technologies for detecting and locating the inner-faults of three-phase squirrel-cage induction motors." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148534.

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Gori, Valentina. "Materiali e umidità di risalita nella basilica di S. Maria Maggiore a Bologna: uno studio sperimentale ai fini del restauro." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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La chiesa di Santa Maria Maggiore è uno degli edifici religiosi più antichi di Bologna. Ormai dal 2012 lo Studio di progettazione Cavina Terra architetti si sta occupando dell’intervento di restauro, volto perlopiù a mitigare i problemi di natura strutturale, occorsi già a seguito degli eventi sismici del febbraio 2012. Il presente lavoro di tesi riguarda i problemi generati dall’umidità di risalita, che ha indotto numerosi fenomeni di degrado non solo sulle superfici delle strutture in elevazione intonacate, ma anche sui basamenti in marmo presenti, nonché sull’estesa pavimentazione in terra
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Amato, Benedetta <1984&gt. "Studio comparativo in vitro dei meccanismi di sopravvivenza di M.bovis e M.avium subsp. paratuberculosis. Valutazione precoce, ai fini diagnostici, dei profili di espressione proteica di macrofagi infettati sperimentalmente." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amsdottorato.unibo.it/8648/1/tesi%20benedetta%20amato%20dottorato%20XXX%20ciclo%20.pdf.

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La tubercolosi bovina e la paratubercolosi sono due patologie che costituiscono un importante minaccia per la salute umana ed animale. Il presente lavoro si basa sullo studio dei prodotti proteici e dei profili di espressione genica di macrofagi di specie bovina e caprina infettati con ceppi di M.bovis e M.paratuberculosis a differenti concentrazioni. Lo scopo è quello di individuare potenziali biomarkers da utilizzare a scopo diagnostico e chiarire le fasi patogenetiche precoci relative all’interazione macrofago-micobatterio. A tal proposito sono stati standardizzati due protocolli di preliev
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Beka, Be Nguema Marius. "Comportement de l'opérateur humain face à une situation dégradée et imprévue : contribution à la réalisation d'une interface homme-machine tolérante à certaines erreurs humaines." Valenciennes, 1994. https://ged.uphf.fr/nuxeo/site/esupversions/3e915137-f166-4513-adfd-f97943c83baf.

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La complexité de la tâche d'un opérateur humain et la variabilité de sa charge de travail, dans un système homme machine, peuvent le conduire à commettre des erreurs aux conséquences graves. Aussi, l'impossibilité de les éliminer dans leur totalité rend nécessaire la présence d'une interface tolérante à ces erreurs, capable d'empêcher leurs conséquences sur le système homme-machine. Le thème de cette recherche consiste donc à analyser le comportement de l'opérateur humain en surcharge mentale ou face à une dégradation plus ou moins importante des informations d'un procédé simule simple de régl
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ISAKSSON, LARS JOHANNES. "HYBRID DEEP LEARNING AND RADIOMICS MODELS FOR ASSESSMENT OF CLINICALLY RELEVANT PROSTATE CANCER." Doctoral thesis, Università degli Studi di Milano, 2022. https://hdl.handle.net/2434/946529.

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Precision medicine holds the potential to revolutionize healthcare by providing every patient with personalized treatments and decisions tailored to his or her individual needs. This might be enabled by the large influx of potentially diagnostic information from new sources such as genetics and modern imaging techniques, provided the relevant information can be extracted. One such framework that has started to demonstrate promise in radiology, especially in the assessment of cancer, is radiomics; the practice of characterizing images by extracting a substantial amount of quantitative mathemati
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Books on the topic "AI Diagnostics"

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Anbarasan, Kalaivani. AI Innovation in Medical Imaging Diagnostics. IGI Global, 2020.

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Anbarasan, Kalaivani. AI Innovation in Medical Imaging Diagnostics. IGI Global, 2020.

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Anbarasan, Kalaivani. AI Innovation in Medical Imaging Diagnostics. IGI Global, 2020.

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Anbarasan, Kalaivani. AI Innovation in Medical Imaging Diagnostics. IGI Global, 2020.

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Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry. IGI Global, 2024.

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Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry. IGI Global, 2024.

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Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry. IGI Global, 2024.

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Rahman, Mahmudur, ed. Artificial Intelligence (AI) and Machine Learning (ML) in Medical Imaging Informatics towards Diagnostic Decision Making. MDPI, 2023. http://dx.doi.org/10.3390/books978-3-0365-8129-3.

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Alexander, Daniel C., M. Jorge Cardoso, Carl-Fredrik Westin, and Sebastien Ourselin. Information Processing in Medical Imaging: 24th International Conference, IPMI 2015, Sabhal Mor Ostaig, Isle of Skye, UK, June 28 - July 3, 2015, Proceedings. Springer London, Limited, 2015.

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Book chapters on the topic "AI Diagnostics"

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Afa, Mahfooz Alam, and Marghoob Enam. "AI-infused respiratory diagnostics." In Soft Computing and Machine Learning. CRC Press, 2025. https://doi.org/10.1201/9781003606055-11.

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Mhlanga, David. "Medical Imaging and Diagnostics." In AI in Hospital Administration. CRC Press, 2025. https://doi.org/10.1201/9781003475804-5.

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Lara, James. "AI-Powered Laboratory Diagnostics Technology." In Recent Advancements in the Diagnosis of Human Disease. CRC Press, 2024. http://dx.doi.org/10.1201/9781003438595-1.

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Ploug, Thomas, and Søren Holm. "Right to Contest AI Diagnostics." In Artificial Intelligence in Medicine. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58080-3_267-1.

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Ploug, Thomas, and Søren Holm. "Right to Contest AI Diagnostics." In Artificial Intelligence in Medicine. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-64573-1_267.

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Vostokov, Dmitry. "Elementary Diagnostics Patterns." In Python Debugging for AI, Machine Learning, and Cloud Computing. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9745-2_3.

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Santra, Debarpita. "Oncology Informatics, AI, and Drug Discovery." In Cancer Diagnostics and Therapeutics. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4752-9_20.

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Kumar, Suneel, and Dashrath Singh. "AI in Diagnostics and Disease Prediction." In Bioinformatics and Beyond. CRC Press, 2025. https://doi.org/10.1201/9781003508403-7.

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Tian, Yuchi, Temitope Emmanuel Komolafe, and Wenxiu Zhang. "AI Applications in Diagnostics and Treatment." In Modern Technologies in Healthcare. CRC Press, 2025. https://doi.org/10.1201/9781003481959-4.

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Milan, Lisa. "Artificial Intelligence and Machine Learning in Integrated Diagnostic." In Integrated Diagnostics and Theranostics of Thyroid Diseases. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35213-3_2.

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AbstractArtificial intelligence (AI) and machine learning (ML) in the medical field have the potential to revolutionize the way in which diseases are detected and treated. Exploiting advanced algorithms and techniques, AI-based systems can analyze a very large amount of medical data and identify patterns that may not be detectable to human experts. This can lead to more accurate and efficient diagnoses, as well as the development of new diagnostic/prognostic methods. Integrated diagnostics combines multiple diagnostic modalities and data sources to provide a more comprehensive understanding of
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Conference papers on the topic "AI Diagnostics"

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Pěnička, Jan, and Josef Števuljak. "AI military vehicle diagnostics." In 2025 International Conference on Military Technologies (ICMT). IEEE, 2025. https://doi.org/10.1109/icmt65201.2025.11061275.

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Pal, Sachin, Tanushka, Kanishka Jha, and Deepika Sharma. "Blockchain-Enhanced AI Diagnostics in Healthcare." In 2024 International Conference on Emerging Technologies and Innovation for Sustainability (EmergIN). IEEE, 2024. https://doi.org/10.1109/emergin63207.2024.10961743.

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Geetha Lakshmi, V. Sai, M. Devika Rani, and K. Bhavana. "AI-Improved Battery-Powered Automobile Battery Diagnostics." In 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT). IEEE, 2024. http://dx.doi.org/10.1109/iccpct61902.2024.10673152.

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Jihane, Benbrik, Rattal Salma, Ghoumid Kamal, and Ar-Reyouchi El Miloud. "Advancing Healthcare Diagnostics with a Hybrid AI Model." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933484.

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Sahu, Santhoshini, Bura Vijay Kumar, Swapna Narla, Balajee Maram, Rohan Raj Maram, and Sreekar Peddi. "Creative AI Approaches to Biomedical Imaging: Revolutionizing Diagnostics." In 2024 First International Conference on Data, Computation and Communication (ICDCC). IEEE, 2024. https://doi.org/10.1109/icdcc62744.2024.10961390.

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Kumar, K. Antony, Charan Appala, Manikandan N. K, Praveen Royal Balaiahgari, and Shreya Balurgi. "Echovision AI-Predictive Deep Learning for Cardiovascular Diagnostics." In 2025 International Conference on Data Science and Business Systems (ICDSBS). IEEE, 2025. https://doi.org/10.1109/icdsbs63635.2025.11031503.

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Santhi, S., M. Murugan, Nandhiha V, Vivitha S, and Karthikeyan D. "Cocoscan: AI-Powered Precision Diagnostics for Coconut Leaf Disease." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933306.

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Bhashkar, Anurag, and Kanwarpartap Singh Gill. "AI Meets Hematology: Enhanced Bone Marrow Diagnostics with EfficientNetB5." In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). IEEE, 2024. https://doi.org/10.1109/aece62803.2024.10911382.

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Ahmed, Zahid, Abha Pandey, Ashish Sharma, Anisha Tandon, Teena, and Sujeet Kumar. "Optimizing Real-Time Medical Diagnostics with Adaptive AI Algorithm." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828588.

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Bhashkar, Anurag, Kanwarpartap Singh Gill, and G. Sunil. "Redefining Bone Marrow Diagnostics With AI-Driven EfficientNetB5 Technology." In 2024 9th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2024. https://doi.org/10.1109/icces63552.2024.10859592.

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Reports on the topic "AI Diagnostics"

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Pasupuleti, Murali Krishna. AI and Quantum-Nano Frontiers: Innovations in Health, Sustainability, Energy, and Security. National Education Services, 2025. https://doi.org/10.62311/nesx/rr525.

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Abstract: This research report explores transformative advancements at the intersection of Artificial Intelligence (AI), Quantum Computing, and Nanotechnology, focusing on breakthrough innovations in health, sustainability, energy, and global security. By integrating quantum algorithms, AI-driven analytics, and advanced nanomaterials, this report highlights revolutionary solutions in precision medicine, predictive diagnostics, sustainable energy storage, universal water purification, and cybersecurity. Real-world case studies and emerging technologies such as graphene-based nanomaterials, quan
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WANG, MIN, Sheng Chen, Changqing Zhong, et al. Diagnosis using artificial intelligence based on the endocytoscopic observation of the gastrointestinal tumours: a systematic review and meta-analysis. InPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.2.0096.

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Review question / Objective: With the development of endoscopic techniques, several diagnostic endoscopy methods are available for the diagnosis of malignant lesions, including magnified pigmented endoscopy and narrow band imaging (NBI).The main goal of endoscopy is to achieve the real-time diagnostic evaluation of the tissue, allowing an accurate assessment comparable to histopathological diagnosis based on structural and cellular heterogeneity to significantly improve the diagnostic rate for cancerous tissues. Endocytoscopy (ECS) is based on ultrahigh magnification endoscopy and has been app
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Alhaddad, Hasan, Zainab Bu Hamad, Sarah Bukhamsin, et al. AI at the Frontline: Unmasking Diagnostic Accuracy in Primary Care Triage — A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2025. https://doi.org/10.37766/inplasy2025.4.0101.

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SAINI, RAVINDER, AbdulKhaliq Alshadid, and Lujain Aldosari. Investigation on the application of artificial intelligence in prosthodontics. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.12.0096.

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Review question / Objective: 1. Which artificial intelligence techniques are practiced in dentistry? 2. How AI is improving the diagnosis, clinical decision making, and outcome of dental treatment? 3. What are the current clinical applications and diagnostic performance of AI in the field of prosthodontics? Condition being studied: Procedures for desktop designing and fabrication Computer-aided design (CAD/CAM) in particular have made their way into routine healthcare and laboratory practice.Based on flat imagery, artificial intelligence may also be utilized to forecast the debonding of dental
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Shah, Syed Zaigham Ali. Breast Cancer Early Detection and Awareness through Community Outreach and AI-Based Diagnostic Tools in Gilgit Baltistan, Pakistan. ResearchHub Technologies, Inc., 2025. https://doi.org/10.55277/researchhub.8zb0qpfi.

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Qin, Ling, Qiyu Liu, Hui Wang, and Lipeng Sun. Accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.12.0072.

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Review question / Objective: This meta-analysis aimed to determine the accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases. Eligibility criteria: Type of study. This study will only include high quality clinical cohort or case control studies. Type of patients. The patients should be those who had undergone breast diseases. Intervention and comparison. This study compares AI with pathology for diagnosing breast diseases. Type of outcomes. The primary outcomes include sensitivity, specificity, positive and negative likelihood ratio, diagnostic odds ratio, and the ar
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Alharbi, Shuaa S., and Haifa F. Alhasson. Toward the Identification of Applications of Artificial Intelligence for Dental Image Detection: Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0023.

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Review question / Objective: The purpose of this systematic review is to understand and compare the current applications of machine learning in the care of dental patients. This will enable us to assess their diagnostic and prognostic accuracy. As part of the study, we will identify areas of development for ML applications in the dental care field. In addition, we will suggest improvements to research methodology that will facilitate the implementation of ML technologies in services and improve clinical treatment guidelines based on the results of future studies. Condition being studied: This
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Pinchuk, O. P., and A. A. Prokopenko. Model of a computer-orient-ed methodological system for the development of digital competence of officers of the military administration of the Armed Forces of Ukraine in the system of qualification improvement. Національна академія Державної прикордонної служби України імені Б. Хмельницького, 2023. http://dx.doi.org/10.33407/lib.naes.736836.

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Pedagogical modeling of modern educational environments remains an urgent task of educational sciences. Research on the formation and development of digital competence of specialists, although they have common features, differ and acquire characteristic features depending on the field of application. This is due to the focus on mastering specific professional skills and increasing the professional level. We found out that, compared to the social and humanitarian sphere and medicine, the development of digital competence of specialists in the military and defense industry is little discussed in
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