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Advances in Lung Cancer Diagnosis

This special issue belongs to the section “Medical Imaging and Theranostics“.

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of the latest advancements and innovations in the diagnosis of lung cancer. Lung cancer remains one of the most challenging cancers to diagnose and treat, necessitating continual improvements in diagnostic methodologies to enhance early detection, accuracy, and personalized care. This Special Issue will explore a wide range of cutting-edge topics, from the integration of artificial intelligence and robotic technologies in diagnostic procedures to the development of novel biomarkers and imaging techniques.

This collection of articles aims to inform and guide healthcare professionals, researchers, and policymakers in their efforts to enhance lung cancer diagnostic practices and ultimately improve patient outcomes.

The scope of this Special Issue includes, but is not limited to, the following:

  1. Developments in low-dose CT screening;
  2. Biomarkers for nodule risk assessment;
  3. Artificial intelligence in lung cancer diagnosis;
  4. Robotic bronchoscopy;
  5. Intra-procedural bronchoscopic imaging;
  6. Advances in endobronchial ultrasound (EBUS);
  7. Quality indicators in lung cancer diagnosis;
  8. Molecular and genetic profiling for personalized diagnosis;
  9. Optimizing tissue acquisition for molecular and genetic profiling of lung cancer.

Dr. Houssein Youness
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • lung cancer
  • diagnosis
  • biomarkers
  • artificial intelligence
  • machine learning
  • robotic bronchoscopy
  • bronchoscopic imaging
  • endobronchial ultrasound (EBUS)
  • quality indicators
  •  molecular profiling
  •  genetic profiling
  •  next-generation sequencing (NGS)
  •  tissue acquisition
  •  low-dose CT screening
  •  early detection
  •  risk assessment
  •  personalized medicine
  •  diagnostic accuracy
  •  medical imaging
  •  lung nodules

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Published Papers

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Diagnostics - ISSN 2075-4418