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Relevant bibliographies by topics / Lung Disease Detection

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Academic literature on the topic 'Lung Disease Detection'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Lung Disease Detection"

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Vidyasri S., Et al. "Automated Lung Disease Detection and Classification Using Quantum Glowworm Swarm Optimizer with Quasi Recurrent Neural Network on Chest X-Ray Images." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1150–59. http://dx.doi.org/10.17762/ijritcc.v11i10.8636.

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Lung diseases or otherwise called respiratory diseases are airborne diseases that affect the lungs and the other tissues of the lungs. Tuberculosis, Coronavirus Disease 2019 (COVID-19), and Pneumonia are a few instances of lung diseases. If the lung disease is diagnosed and treated in the initial stage, the chances of recovery rate and long-term survival rates can be increased. Usually, lung disease is identified by Chest X-Ray (CXR) image examination, skin test, sputum sample test, Computed Tomography (CT) scan examination, and blood test. Because of its non-invasive and convenient evaluation

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Tikendra, Sahu, and S. Choubey Aakanksha. "A review on lungs disease detection using image processing." i-manager's Journal on Information Technology 11, no. 1 (2022): 48. http://dx.doi.org/10.26634/jit.11.1.18536.

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The global fitness company estimates that by 2030, Chronic Obstructive Pulmonary Disease (COPD) will be the third leading cause of death in the world. Computerized Tomography (CT) of the lungs includes a number of structures that may be important in the prognosis and evaluation of lung disease. CT images of the lungs show a section of the chest that constitutes a large number of systems, including blood vessels, arteries, respiratory vessels, pulmonary pleura, and parenchyma, each with its own information. For this reason, the phasing of the lung systems is very important for the analysis and

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Acharya, Dipanjan, K. Eashwer, Soumya Kumar, R. Sivakumar, P. C. Kishoreraja, and Ramasamy Srinivasagan. "Multiple Disease Detection using Machine Learning Techniques." International Journal of Online and Biomedical Engineering (iJOE) 19, no. 13 (2023): 120–37. http://dx.doi.org/10.3991/ijoe.v19i13.40523.

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The COVID-19 disease outbreak resulted in a worldwide pandemic. Currently, the reverse transcription-polymerase chain reaction (RT-PCR), which relies on nasopharyngeal swabs to examine the existence of the ribonucleic acid (RNA) of SARS-CoV-27, is still a popular approach to testing for the disease. Despite the high level of specificity of testing with RT-PCR, the sensitivity of the method could be relatively low, and there is significant variability in efficacy depending on different sampling methods and the time of occurrence of symptoms. It is therefore essential for us to develop a machine

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Chen, Taiyang. "Application of Machine Learning in Lung Disease Detection: A Review." Theoretical and Natural Science 89, no. 1 (2025): 188–93. https://doi.org/10.54254/2753-8818/2025.21453.

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Lung disease remains the leading cause of global mortality, which requires efficient and accurate methods for detection. Recent advancements in machine learning algorithms, artificial intelligence and image analysis technologies offer potential for early diagnosis and improved patient outcomes. This review summarizes different types of medical images that can be or have been frequently used in lung disease diagnosis, such as chest X-rays and CT scans. The paper then explores the role of key machine learning techniques in detecting various lung diseases, such as lung cancer, pneumonia and tuber

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Dubey, Sakshi. "Pulmonary Disease Prediction by Using Machine Learning Technique." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem46795.

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Abstract - Pulmonary Disease is one of the leading causes of Cancer related deaths world wide and its early diagnosis and treatment are essential to cure the patient normally indicated by small growths in the lungs called nodules. It usually happens because cells in the lungs start increasing uncontrollably. Finding these Lung nodules is important for detecting lung Cancer, these nodules are typically detected through CT scans, but manual interpretation can be time-consuming and prone to human error. Through a process of feature extraction and selection, our model was trained to identify patte

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Prabu, S. Manikanda. "Automatic Detection of Lung Disease Using Machine Learning." Bonfring International Journal of Advances in Image Processing 14, no. 1 (2024): 8–10. https://doi.org/10.9756/bijaip/v14i1/bij24013.

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Medical image analysis is crucial for the early detection of lung illness, assisting doctors in providing appropriate therapies, and preventing fatalities. In this paper, an automated system is developed by fusing metaheuristic algorithm and machine learning classifier to differentiate between heathy lungs and affected lungs. The developed system has four phases such as preprocessing, feature extraction, feature selection, and classification. In the first phase, affected region is isolated from its background using thresholding method. The segmented image is used to construct the second phase'

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Sowmya, Veeramalla. "Lung Disease Detection Using CNN." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 4042–49. http://dx.doi.org/10.22214/ijraset.2021.35595.

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Covid Pneumonia is a life-threatening bacterial disease in humans that affects one or both lungs and is caused by the bacteria Streptococcus pneumonia. Also known as Covid-19, this is a respiratory illness that was first discovered in Wuhan, China. Expert radiotherapists must evaluate chest X-rays used to diagnose pneumonia. As a result, establishing an autonomous system for detecting pneumonia would be advantageous for treating the condition quickly, especially in distant places. The statistical results show that using pre trained CNN models and supervised classifier algorithms to analyse che

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Hassan, Umaisa, Amit Singhal, and Priyanshu Chaudhary. "Lung disease detection using EasyNet." Biomedical Signal Processing and Control 91 (May 2024): 105944. http://dx.doi.org/10.1016/j.bspc.2024.105944.

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ANWAR, MR, MA BAKAR, HM AWAIS, et al. "EARLY DETECTION OF LUNGS CANCER USING MACHINE LEARNING ALGORITHMS." Biological and Clinical Sciences Research Journal 2023, no. 1 (2023): 187. http://dx.doi.org/10.54112/bcsrj.v2023i1.187.

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Medical healthcare systems store a large amount of clinical data about patients related to their biographies and disease information. Doctors use clinical data for the early detection of diseases that helps with proper patients’ treatments to save their lives. These clinical systems are helpful in detecting cancer diseases at early stages to save people's lives. Lung cancer is the third largely spreading disease in human beings all over the globe, which may lead so many people to death because of inaccurate detection of their disease at the initial stages. Therefore, this study will help docto

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Kasuga, Ikuma, Yoshimi Yokoe, Sanae Gamo, et al. "Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries." Medicine 103, no. 19 (2024): e38161. http://dx.doi.org/10.1097/md.0000000000038161.

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Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early det

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Dissertations / Theses on the topic "Lung Disease Detection"

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Al-Hillawi, Abdul Hadi Sadiq. "The role of exercise tests in the detection and management of lung disease." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/38217.

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Chaung, Monica. "Role of Lung Clearance Index in the Early Detection of Pulmonary Changes in Children with Sickle Cell Disease." Thesis, The University of Arizona, 2018. http://hdl.handle.net/10150/627163.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.<br>Pulmonary complications including acute chest syndrome are leading causes of sickle cell disease related morbidity and mortality. Studies have shown that pulmonary changes can be detected during childhood. Spirometry is the current standard for measuring lung function. Growing evidence suggests that lung clearance index (LCI) is as sensitive as spirometry in identifying pulmonary changes in pediatric patients. Our cross-section

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Paun, Mihaela. "Detecting genetic variants in radiation-induced lung disease." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119560.

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Thoracic radiotherapy, a common treatment modality for thoracic cancers, has pulmonary side-effects of either excessive inflammation (alveolitis), or pulmonary fibrosis consisting of uncontrolled deposition of collagen in the lungs, for which no cure exists. Prior knowledge, before radiotherapy, of patients genetically predisposed to fibrosis would improve cancer treatments. Based on the known similarities between human and mouse responses to lung irradiation, we used a murine model to detect molecular pathways, immune mechanisms and genetic variants associated with the development of fibrosis

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Chassagnon, Guillaume. "AI-driven Detection, Characterization and Classification of Chronic Lung Diseases." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC101.

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L’évaluation de la gravité et la surveillance des maladies pulmonaires chroniques représentent deux challenges importants pour la prise en charge des patients et l’évaluation des traitements. La surveillance repose principalement sur les données fonctionnelles respiratoires mais l’évaluation morphologique reste un point essentiel pour le diagnostic et l’évaluation de sévérité. Dans la première partie de cette thèse, nous proposons différents modèles pour quantifier la sévérité de pathologies bronchiques chroniques au scanner. Une approche simple par seuillage adaptatif et une méthode plus soph

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Jayasuriya, Rathnini. "Emerging tools for detecting impairment in paediatric obstructive lung disease." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/22001.

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Background and aims Respiratory disease is an important cause of mortality and morbidity in the paediatric population. Respiratory diseases affecting the airways can be diagnosed using pulmonary function tests (PFTs) but these tests can be challenging in paediatrics. Commonly used PFTs in paediatrics include spirometry, whole body plethysmography (WBP) and diffusing capacity of carbon monoxide (DLCO). Of these tests, spirometry provides the most detailed information about airway function; however, it does not provide information regarding peripheral airway function or ventilation. Emerging too

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Pavelescu, Adriana. "Echocardiography for the noninvasive study of the pulmonary circulation: applications to the study of right ventricular effects of targeted therapies of pulmonary hypertension, limiting factors to exercise capacity, and detection of early pulmonary vascular disease in healthy subjects." Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209616.

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Ce travail a été consacré à l’étude non invasive de la circulation pulmonaire normale par mise en œuvre de l’échocardiographie Doppler. <p>En intégrant les mesures obtenues dans une approche physiopathologique, et en exploitant les nouvelles possibilités d’échocardiographes portables, techniquement performants, nous avons analysé les effets d’un inhibiteur de la phosphodiestérase-5 et d’une prostacycline, pour tenter d’en identifier d’éventuels effets introtropes intrinsèques, nous avons exploré le concept de réserve vasculaire pulmonaire comme facteur limitant de l’aptitude aérobie et indice

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Li, Lei. "Deep learning and SVM methods for lung diseases detection and direction recognition." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950631.

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Mills, Ross Jack. "Autoantibodies in ILD : detection and association of anti-Hsp72 IgG complexes in IPF." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/29615.

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Background Idiopathic pulmonary fibrosis (IPF) is one of a number of interstitial lung diseases (ILDs) that result in extensive and chronic pulmonary fibrosis. In IPF pathology, immunological dysfunction has been identified as a contributing factor to the ongoing fibrotic process, implicating cells and mechanisms of both the innate and humoral immune response. Due to the complex and diverse range of cells and mediators involved in IPF, the pathology is still poorly understood. Evidence of complement activation through the classical pathway in IPF lungs implies a role for IgG in the pathology.

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Manitz, Juliane. "Statistical Inference for Propagation Processes on Complex Networks." Doctoral thesis, 2014. http://hdl.handle.net/11858/00-1735-0000-0022-5F38-B.

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Die Methoden der Netzwerktheorie erfreuen sich wachsender Beliebtheit, da sie die Darstellung von komplexen Systemen durch Netzwerke erlauben. Diese werden nur mit einer Menge von Knoten erfasst, die durch Kanten verbunden werden. Derzeit verfügbare Methoden beschränken sich hauptsächlich auf die deskriptive Analyse der Netzwerkstruktur. In der hier vorliegenden Arbeit werden verschiedene Ansätze für die Inferenz über Prozessen in komplexen Netzwerken vorgestellt. Diese Prozesse beeinflussen messbare Größen in Netzwerkknoten und werden durch eine Menge von Zufallszahlen beschrieben. Alle vorge

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Pavel, Ana Brandusa. "Multi-omics data integration for the detection and characterization of smoking related lung diseases." Thesis, 2017. https://hdl.handle.net/2144/24073.

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Lung cancer is the leading cause of death from cancer in the world. First, we hypothesized that microRNA expression is altered in the bronchial epithelium of patients with lung cancer and that incorporating microRNA expression into an existing mRNA biomarker may improve its performance. Using bronchial brushings collected from current and former smokers, we profiled microRNA expression via small RNA sequencing for 347 patients with available mRNA data. We found that four microRNAs were under-expressed in cancer patients compared to controls (p<0.002, FDR<0.2). We explored the role of these m

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Books on the topic "Lung Disease Detection"

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Canadian Institute for Radiation Safety. CAIRS early lung cancer detection program: Report. CARIS, Canadian Institute for Radiation Safety, 1989.

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Lung Cancer. Exon Publications, 2024. https://doi.org/10.36255/lung-cancer.

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Lung cancer is a serious and common disease that begins in the lungs, often caused by smoking, environmental exposures, or genetic factors. This article discusses lung cancer, offering information for patients, caregivers, and the general public. It begins by explaining what lung cancer is, its types, and the risk factors associated with its development. The article explores symptoms and how the disease progresses, along with the challenges of early detection. Key sections cover the pathophysiology of lung cancer, detailing how genetic mutations and environmental factors lead to tumor growth.

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Tuxen, David V. Pathophysiology and causes of airflow limitation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0110.

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Exacerbations of asthma or chronic obstructive pulmonary disease (COPD) can be life-threatening emergencies, and require careful management to minimize the risks of morbidity and mortality. Prompt, full bronchodilator therapy, careful observation and appropriate mechanical ventilation technique is required. Dynamic hyperinflation of the lungs occurs in all patients, and must be careful assessed and regulated. Excessive dynamic hyperinflation can result in respiratory tamponade, hypotension, circulatory failure, pneumothoraces and, in severe cases, cardiac arrest. Intravenous or continuous nebu

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Coronado, Gloria D. Cancer Detection and Screening. Edited by David A. Chambers, Wynne E. Norton, and Cynthia A. Vinson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190647421.003.0013.

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Lung and colorectal cancers account for high numbers of preventable deaths. Because of this, scaling up effective interventions to increase routine screening and lower tobacco use is critically important. Screening programs for these diseases vary greatly in their anticipated outcomes. Colorectal cancer screening can both prevent colorectal cancer and identify it in early, treatable stages. Screening for lung cancer, on the other hand, cannot prevent most lung cancer-related deaths, and up to 80% of deaths could be averted from smoking cessation. In this complicated environment for ongoing ref

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Park, John G. Diagnosis and Common Disorders. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780199755691.003.0616.

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Common symptoms of pulmonary disease include cough, sputum, hemoptysis, dyspnea, chest pain, cyanosis, and clubbing. A thorough history and physical examination, including palpation, auscultation, and percussion, are key to accurate diagnosis. The radiologic tests performed in the diagnosis of chest diseases include plain CXR, CT, magnetic resonance imaging, pulmonary angiography, and bronchial angiography. Simple microscopy with a "wet" slide preparation of sputum is helpful in assessing the degree of sputum eosinophilia and detecting the presence of Charcot-Leyden crystals. The major indicat

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Madhu, G., Sandeep Kautish, A. Govardhan, and Avinash Sharma, eds. Emerging Computational Approaches in Telehealth and Telemedicine: A Look at The Post-COVID-19 Landscape. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150792721220101.

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This book gives an overview of innovative approaches in telehealth and telemedicine. The Goal of the content is to inform readers about recent computer applications in e-health, including Internet of Things (IoT) and Internet of Medical Things (IoMT) technology. The 9 chapters will guide readers to determine the urgency to intervene in specific medical cases, and to assess risk to healthcare workers. The focus on telehealth along with telemedicine, encompasses a broader spectrum of remote healthcare services for the reader to understand. Chapters cover the following topics: - A COVID-19 care s

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Gargani, Luna, and Marcelo-Haertel Miglioranza. Lung ultrasound. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0016.

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The lung is a relatively new site for the application of ultrasound. Beyond the more established assessment of pleural effusion, this organ has been traditionally considered off limits for sonographic investigation, since air is a well-known foe of the ultrasound beam. However, in recent years it has been shown that this apparent physical limitation can be overcome when the air content decreases, as happens in a diseased pulmonary parenchyma. The most useful lung ultrasound sign for cardiologists is the presence of B-lines, the sonographic hallmark of pulmonary interstitial syndrome, including

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Hirsch, Fred R., Jr Paul A. Bunn, James L. Mulshine, and Harubumi Kato. IASLC Textbook of Prevention and Early Detection of Lung Cancer. Informa Healthcare, 2005.

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Rao, Chethan P. Venkatasubba, and Jose Ignacio Suarez. Management of non-traumatic subarachnoid haemorrhage in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0239.

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Non-traumatic subarachnoid haemorrhage (ntSAH) is a complex disease affecting multiple systems and the hospital course of affected patients can be variable. ntSAH is associated with high morbidity and mortality, with the causes of early deaths being either rebleeding or hydrocephalus. The risk of rebleeding is reduced by immediate control of arterial blood pressure and early securing of ruptured aneurysms by either endovascular coiling or surgical clipping. Ongoing management focuses on prevention, detection, and management of delayed neurological deficits. Current recommendations include prop

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Reddy, Ugan, and Nicholas Hirsch. Diagnosis, assessment, and management of myasthenia gravis and paramyasthenic syndromes. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0244.

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Diseases that affect the neuromuscular junction (NMJ) interfere with normal nerve transmission and cause weakness of voluntary muscles. The two most commonly encountered are acquired myasthenia gravis (MG) and the Lambert–Eaton myasthenic syndrome (LEMS). Acquired MG is an autoimmune disease in which antibodies are directed towards receptors at the NMJ. In 85% of patients, IgG antibodies against the postsynaptic acetylcholine receptor (AChR) are found (seropositive MG). The thymus gland appears to be involved in the production of these which cause an increase rate of degradation of AChR result

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Book chapters on the topic "Lung Disease Detection"

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Sharma, Kaushik Das, Subhajit Kar, and Madhubanti Maitra. "Intelligent Computing Approach for Lung Nodule Detection." In Intelligent Computing in Carcinogenic Disease Detection. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2424-6_7.

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Dettmar, Peter W., Rhianna K. Lenham, Adrian J. Parkinson, and Andrew D. Woodcock. "Pepsin Detection as a Diagnostic Test for Reflux Disease." In Reflux Aspiration and Lung Disease. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90525-9_8.

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Batra, Neera, Sonali Goyal, and Kritika Chhabra. "Lung Disease Detection Using Machine Learning Approach." In International Conference on Innovative Computing and Communications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2821-5_21.

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Elbehairy, Amany F., and Ahmed Sadaka. "Early Detection of Chronic Obstructive Pulmonary Disease: Influence on Lung Cancer Epidemiology." In Lung Imaging and CADx. CRC Press, 2019. http://dx.doi.org/10.1201/9780429055959-2.

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Jani, Sk Nageena, J. Vidya, M. Sneha, K. Jaya Shankar, N. Narendra Babu, and K. Sathish. "Respiratory Disease Detection Using Lung Sound with CNN." In Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET 2024). Atlantis Press International BV, 2024. http://dx.doi.org/10.2991/978-94-6463-471-6_84.

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Tran, Huy, Long TonThat, and Kien Trang. "Weighted Box Fusion Ensembling for Lung Disease Detection." In IFMBE Proceedings. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75506-5_60.

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Klein, Jeffrey. "Current Concepts in the Diagnosis and Staging of Lung Cancer." In IDKD Springer Series. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83872-9_3.

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Abstract Diagnostic imaging plays a central role in the evaluation and management of patients with lung cancer. This ranges from screening high-risk current or former smokers with low-dose CT, interpreting imaging studies performed for chest or systemic symptoms showing suspicious abnormalities, the incidental detection of findings in asymptomatic patients that are concerning for lung cancer, providing a clinical stage of disease to help direct diagnostic biopsy, guiding disease management, and assessing the patient’s response to or detecting the complications of treatment. This chapter begins

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Rafii, Saeed, Batool Aboud, and Humaid O. Al-Shamsi. "Lung Cancer in the UAE." In Cancer Care in the United Arab Emirates. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6794-0_33.

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AbstractLung cancer is one of the leading causes of cancer-related mortalities worldwide. It is expected that the incidence of lung cancer will significantly increase in the next decade. Given the recognized risk factors for lung cancer, such as smoking and air pollution, preventative measures can have a remarkable impact on reducing the incidence of lung cancer in the UAE. Additionally, earlier detection of lung cancer can lead to reduced mortality from this disease. In this chapter, we review the current incidence of lung cancer in the UAE compared with the region and the rest of the world,

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Shylaja, C. S., R. Anandan, and A. Sajeev Ram. "Evolution of Lung CT Image Dataset and Detection of Disease." In Intelligent Computing and Innovation on Data Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3284-9_50.

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Katke, Abhishek, Khyati Kulkarni, Rugved Dharmadhikari, Anagha Rajput, Mousami V. Munot, and R. C. Jaiswal. "Lung Disease Detection Based on Deep Learning Techniques: A Review." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1320-2_26.

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Conference papers on the topic "Lung Disease Detection"

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Hajbe, Janhavi R., Sneha K. Patle, Shreya V. Talvekar, Tanvi W. Khonde, and Prajyot R. Yesankar. "ResNet50-Based Deep Learning Model for Lung Disease Detection." In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). IEEE, 2025. https://doi.org/10.1109/icmsci62561.2025.10894373.

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D, Gnanakumar, Sai Dileep G, Ravi Sri Ram G. R. B, Koti Reddy E, and Shamanth E. "Multi-Class Lung Disease Detection Using Resnet50 and Transfer Learning." In 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS). IEEE, 2024. https://doi.org/10.1109/iciics63763.2024.10859399.

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Balapriya, S., Anandaraj B, Sathish Kumar P. J, Surendran R, and K. S. Balamurugan. "Optimizing Early Detection of Lung Disease Through Data-Driven Approaches." In 2025 8th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech). IEEE, 2025. https://doi.org/10.1109/iementech65115.2025.10959696.

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Mehta, Shiva, and Ravi Kumar. "Optimizing Lung Disease Detection through Federated Learning and Convolutional Neural Networks." In 2024 5th IEEE Global Conference for Advancement in Technology (GCAT). IEEE, 2024. https://doi.org/10.1109/gcat62922.2024.10924138.

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Ariesh, G. K., T. Hariharan, S. Kavin, and S. B. Thamarai Selvi. "Deep Learning and Fuzzy Integration for Lung Disease Detection using VGG16." In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2025. https://doi.org/10.1109/sceecs64059.2025.10941567.

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Khan, Kashaf, and Abdul Aleem. "Lung Disease Detection Using CNNs and Transfer Learning on Medical Imaging." In 2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI). IEEE, 2025. https://doi.org/10.1109/iccsai64074.2025.11063806.

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Liewarnata, Edgar Caesar, Yosica Mariana, Sofyan Tan, Suryadiputra Liawatimena, and Winda Astuti. "Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)." In 2024 7th International Conference of Computer and Informatics Engineering (IC2IE). IEEE, 2024. http://dx.doi.org/10.1109/ic2ie63342.2024.10747899.

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M, Ramadevi, MO Ramkumar, D. Jayakumar, R. Rajmohan, and A. Arunkumar. "An Early Lung Disease Detection and Classification Using Bidirectional Deep Learning Over Masked Autoencoder." In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). IEEE, 2025. https://doi.org/10.1109/icmsci62561.2025.10894160.

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Kansal, Kajal, and Kanika Kansal. "A Transfer Learning based Deep Learning Framework for Lung Disease Detection Utilizing CXR Images." In 2025 International Conference on Intelligent Control, Computing and Communications (IC3). IEEE, 2025. https://doi.org/10.1109/ic363308.2025.10957266.

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Khan, Kashaf, and Abdul Aleem. "A Hybrid Approach Combining YOLO and Deep Neural Networks for Efficient Lung Disease Detection." In 2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI). IEEE, 2025. https://doi.org/10.1109/iccsai64074.2025.11064147.

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Reports on the topic "Lung Disease Detection"

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Sriuranpong, Virote. The role of SHP-1 promoter 2 hypermethylation detection of lymph node micrometastasis in resectable nonmetastasis NSCLC as a prognostic marker of disease. Chulalongkorn University, 2010. https://doi.org/10.58837/chula.res.2010.16.

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Introduction; Despite adequate surgical management of stage I non-small cell lung cancer, many patients still have relapsed of disease which leads to mortality. Micrometastasis of tumor is the postulate mechanism which might not be detected by standard H&E method. The author conducted the study of epithelial methylation marker, SHP-1 Promoter 2 (SHP1P2) methylation as a potential molecular marker to detect high risk relapsed of disease in stage I resectable non-small cell lung cancer (NSCLC). Method; To explore the potential role of SHP1P2 methylation to detect micrometastasis, Lymph node

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ZHAO, JIE, LIANHUA YE, WEI WANG, YANTAO YANG, ZHENGHAI SHEN, and SUNYIN RAO. Surgical Prognostic Factors of Second Primary Lung Cancer: A Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0047.

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Review question / Objective: The objective of this study was to explore the effects of different surgical strategies and potential prognostic factors on the prognosis of patients with SPLC through a systematic review and meta-analysis.Prognostic factors included surgical approach, type of SPLC(Synchronous and metachronous),histology,disease-free interval (DFI),tumor size,CT morphology, lymph node metastasis status, smoking status, gender. Condition being studied: With the development of imaging technology and better survival after primary lung cancer, the detection rate of second primary lung

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Rankin, Nicole, Deborah McGregor, Candice Donnelly, et al. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, 2019. http://dx.doi.org/10.57022/clzt5093.

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Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asy

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99mTc SPECT-CT, Consensus QIBA Profile. Chair Yuni Dewaraja and Robert Miyaoka. Radiological Society of North America (RSNA)/Quantitative Imaging Biomarkers Alliance (QIBA), 2019. https://doi.org/10.1148/qiba/20191021.

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The quantification of 99mTc labeled biomarkers can add unique value in many different settings, ranging from clinical trials of investigation new drugs to the treatment of individual patients with marketed therapeutics. For example, goals of precision medicine include using companion radiopharmaceutical diagnostics as just-in-time, predictive biomarkers for selecting patients to receive targeted treatments, customizing doses of internally administered radiotherapeutics, and assessing responses to treatment. This Profile describes quantitative outcome measures that represent proxies of target c

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CT Lung Densitometry, Consensus QIBA Profile. Chair Charles Hatt and Miranda Kirby. • The Publisher is Radiological Society of North America (RSNA)/Quantitative Imaging Biomarkers Alliance (QIBA), 2020. https://doi.org/10.1148/qiba/20200904.

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The goal of a QIBA Profile is to achieve a repeatable and useful level of performance for measures of lung density from quantitative CT using the RA-950 HU and Perc15 biomarkers of emphysema. Please see Appendix C for more detailed information on the calculation of and rationale for RA-950 HU and Perc15 as the biomarkers of choice. The Claim (Section 2) describes the performance in terms of bias and precision of RA-950 HU and Perc15 for detecting change in lung density. The Activities (Section 3) describe how to generate RA-950 HU and Perc15 for longitudinal studies of the change in lung densi

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Questionnaires directed at smokers improve detection of chronic lung disease in general practice. National Institute for Health Research, 2016. http://dx.doi.org/10.3310/signal-000311.

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