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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, "Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases", we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
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Ajouter au panierHardcover. Etat : new. Hardcover. Artificial intelligence (AI) in medical imaging is revolutionizing healthcare by enhancing screening, diagnostics, and clinical care. This integration is crucial as the global healthcare industry strives to enhance accuracy, efficiency, and accessibility. AI and machine learning (ML) extend far beyond simple automation, ushering in an era of precision medicine with diagnostics and treatments tailored to individual patients. Advances in deep learning (DL) further enable rapid analysis of complex imaging data, supporting clinical decisions, reducing diagnostic variability, and facilitating early detection-ultimately leading to improved outcomes. Despite its promise, integrating AI into clinical settings faces challenges. Effective AI models require high-quality, annotated training datasets; yet, the scarcity of such data and the imbalance between cases and controls hinder model development. Moreover, real-world medical datasets often include noisy and incomplete data, which can compromise algorithm reliability and introduce biases. The Special Issue "Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care" highlights groundbreaking advancements in AI/ML for medical imaging. It addresses challenges posed by limited and imperfect data while presenting innovative methodologies for image-based screening, diagnostics, and management. By showcasing original research and reviews, this issue provides valuable insights into state-of-the-art AI applications poised to effectively address global health challenges. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, 'Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases', we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence (AI) in medical imaging is revolutionizing healthcare by enhancing screening, diagnostics, and clinical care. This integration is crucial as the global healthcare industry strives to enhance accuracy, efficiency, and accessibility. AI and machine learning (ML) extend far beyond simple automation, ushering in an era of precision medicine with diagnostics and treatments tailored to individual patients. Advances in deep learning (DL) further enable rapid analysis of complex imaging data, supporting clinical decisions, reducing diagnostic variability, and facilitating early detection-ultimately leading to improved outcomes. Despite its promise, integrating AI into clinical settings faces challenges. Effective AI models require high-quality, annotated training datasets; yet, the scarcity of such data and the imbalance between cases and controls hinder model development. Moreover, real-world medical datasets often include noisy and incomplete data, which can compromise algorithm reliability and introduce biases. The Special Issue 'Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care' highlights groundbreaking advancements in AI/ML for medical imaging. It addresses challenges posed by limited and imperfect data while presenting innovative methodologies for image-based screening, diagnostics, and management. By showcasing original research and reviews, this issue provides valuable insights into state-of-the-art AI applications poised to effectively address global health challenges.
Vendeur : preigu, Osnabrück, Allemagne
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Ajouter au panierBuch. Etat : Neu. Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases | Buch | Gebunden | Englisch | 2023 | MDPI AG | EAN 9783036564340 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Vendeur : preigu, Osnabrück, Allemagne
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Ajouter au panierBuch. Etat : Neu. Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care | Buch | Englisch | 2025 | MDPI AG | EAN 9783725835010 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.