Thoracic diseases refer to disorders that affect the lungs, heart, and other parts of the rib cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis, cardiomegaly, and fracture. Millions of people die every year from thoracic diseases. Therefore, early detection of these diseases is essential and can save many lives. Earlier, only highly experienced radiologists examined thoracic diseases, but recent developments in image processing and deep learning techniques are opening the door for the automated detection of these diseases. In this paper, we present a comprehensive review including: types of thoracic diseases; examination types of thoracic images; image pre-processing; models of deep learning applied to the detection of thoracic diseases (e.g., pneumonia, COVID-19, edema, fibrosis, tuberculosis, chronic obstructive pulmonary disease (COPD), and lung cancer); transfer learning background knowledge; ensemble learning; and future initiatives for improving the efficacy of deep learning models in applications that detect thoracic diseases. Through this survey paper, researchers may be able to gain an overall and systematic knowledge of deep learning applications in medical thoracic images. The review investigates a performance comparison of various models and a comparison of various datasets.
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http://dx.doi.org/10.3390/diagnostics12123034 | DOI Listing |
Echocardiography
January 2025
Department of Medicine and Surgery, University of Milano-Bicocca, Milano, Italy.
ERJ Open Res
January 2025
Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.
Introduction: Achieving an early diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) in pulmonary embolism (PE) survivors results in better quality of life and survival. Importantly, dedicated follow-up strategies to achieve an earlier CTEPH diagnosis involve costs that were not explicitly incorporated in the models assessing their cost-effectiveness. We performed an economic evaluation of 11 distinct PE follow-up algorithms to determine which should be preferred.
View Article and Find Full Text PDFERJ Open Res
January 2025
Department of Infectious Diseases, Respiratory Medicine and Critical Care, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Background: Data regarding the effectiveness and safety of endoscopic lung volume reduction with valves (ELVR) in emphysema patients with a very low 6-min walk test (6MWT) are limited. Patients with severe emphysema and very low exercise capacity, as indicated by a 6MWT ≤140 m, are often excluded from clinical studies on ELVR, assuming limited therapeutic benefits and increased complication risk.
Study Designs And Methods: This study utilised data from the Lungenemphysemregister e.
Nat Chem Biol
January 2025
Fudan University Shanghai Cancer Center, Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Medical Epigenetics, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Chromatin and transcription regulators are critical to defining cell identity through shaping epigenetic and transcriptional landscapes, with their misregulation being closely linked to oncogenesis. Pharmacologically targeting these regulators, particularly the transcription-activating BET proteins, has emerged as a promising approach in cancer therapy, yet intrinsic or acquired resistance frequently occurs, with poorly understood mechanisms. Here, using genome-wide CRISPR screens, we find that BET inhibitor efficacy in mediating transcriptional silencing and growth inhibition depends on the auxiliary/arm/tail module of the Integrator-PP2A complex (INTAC), a global regulator of RNA polymerase II pause-release dynamics.
View Article and Find Full Text PDFCommun Biol
January 2025
Laboratory of Intensive Care, Laboratory for Prevention and Translation of Geriatric Diseases, The Affiliated Hospital of Yangzhou University, Yangzhou, China.
Cellular senescence (CS) is recognized as a critical driver of aging and age-related disorders. Recent studies have emphasized the roles of ion channels as key mediators of CS. Nonetheless, the roles and regulatory mechanisms of chloride intracellular channels (CLICs) during CS remain largely unexplored.
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