Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 25, 2023
PURPOSE: To develop a deep learning model that combines CT and radiation dose (RD) images to predict the occurrence of radiation pneumonitis (RP) in lung cancer patients who received radical (chemo)radiotherapy.
PURPOSE: Most robot-assisted thoracoscopic surgery (RATS) is performed from the vertical view. This study evaluates the initial outcomes of our novel confronting RATS technique, in which the patient was viewed horizontally, as in open thoracotomy.
In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep L...
Technology in navigating to peripheral pulmonary nodules has improved in recent years. The recent integration of a robotic platform using shape-sensing technology and mobile cone-beam computed tomography imaging technology has enhanced confidence in ...
Lung cancer is one of the most common causes of cancer deaths in the modern world. Screening of lung nodules is essential for early recognition to facilitate treatment that improves the rate of patient rehabilitation. An increase in accuracy during l...
BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of lung cancers are non-small cell lung cancer (NSCLC), accounting for approximately 85% of all lung cancer types. The Cox proportional hazards model (CPH),...
International journal of radiation biology
Feb 6, 2023
The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. ...
BACKGROUND: The potential of artificial intelligence (AI) to predict the nature of part-solid nodules based on chest computed tomography (CT) is still under exploration.
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