AIMC Topic: Thoracic Neoplasms
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First-line combination therapy of immunotherapy plus anti-angiogenic drug for thoracic SMARCA4-deficient undifferentiated tumors in AIDS: a case report and review of the literature.
Frontiers in immunology
Jan 9, 2025
BACKGROUND: Thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT) exhibit a notably aggressive phenotype, which is associated with poor patient survival outcomes. These tumors are generally resistant to conventional cytotoxic chemotherapy, ...
Optimizing the management of immune-related adverse events and survival in patients with thoracic cancer receiving immunotherapy through artificial intelligence (electronic patient-reported outcomes): The IMPATHI study.
Bulletin du cancer
Dec 18, 2024
INTRODUCTION: The lung cancer continues to be the primary cause of cancer-related deaths, despite significant advancements in treatment through the introduction of immunological checkpoint inhibitors (ICI). These inhibitors, initially used as monothe...
Enhancing Precision in Cardiac Segmentation for Magnetic Resonance-Guided Radiation Therapy Through Deep Learning.
International journal of radiation oncology, biology, physics
May 24, 2024
PURPOSE: Cardiac substructure dose metrics are more strongly linked to late cardiac morbidities than to whole-heart metrics. Magnetic resonance (MR)-guided radiation therapy (MRgRT) enables substructure visualization during daily localization, allowi...
Propensity-Matched Analysis of the Short-Term Outcome of Robot-Assisted Minimally Invasive Esophagectomy Versus Conventional Thoracoscopic Esophagectomy in Thoracic Esophageal Cancer.
World journal of surgery
Apr 30, 2022
BACKGROUND: In this matched-cohort study, we investigated the short-term outcome of robot-assisted minimally invasive esophagectomy (RAMIE) compared with conventional minimally invasive thoracoscopic esophagectomy (MIE) in esophageal cancer patients.
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.
The Lancet. Digital health
Jul 1, 2021
BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretati...
Mass Screening
Area Under Curve
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Models, Biological
Humans
Radiography, Thoracic
Artificial Intelligence
Deep Learning
Infections
Female
Adolescent
Thoracic Injuries
X-Rays
Young Adult
Aged
Retrospective Studies
ROC Curve
Adult
Aged, 80 and over
Thoracic Neoplasms
Male
Middle Aged
Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.
International journal of computer assisted radiology and surgery
Jun 10, 2021
PURPOSE: Respiratory motion of thoracic organs poses a severe challenge for the administration of image-guided radiotherapy treatments. Providing online and up-to-date volumetric information during free breathing can improve target tracking, ultimate...
Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.
AJR. American journal of roentgenology
Apr 14, 2020
The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. Retrospective review (April-May 2019) of the cases of adults...
A convolutional neural network-based system to classify patients using FDG PET/CT examinations.
BMC cancer
Mar 17, 2020
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...
Towards real-time respiratory motion prediction based on long short-term memory neural networks.
Physics in medicine and biology
Apr 10, 2019
Radiation therapy of thoracic and abdominal tumors requires incorporating the respiratory motion into treatments. To precisely account for the patient's respiratory motions and predict the respiratory signals, a generalized model for predictions of d...
[Robot-assisted Thoracic Surgery for Mediastinal and Chest Wall Tumors:Atypical Surgical Approaches by the Tumor Localization].
Kyobu geka. The Japanese journal of thoracic surgery
Jul 1, 2023
Surgery for mediastinal and chest wall tumors requires various approaches, including open and thoracoscopic, depending on the size and localization of the tumor. While robotic surgery for anterior mediastinal tumors has become a standardized approach...
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