AIMC Topic: Lung Neoplasms
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Segmentation of CT Lung Images Using FCM with Active Contour and CNN Classifier.
Asian Pacific journal of cancer prevention : APJCP
Mar 1, 2022
OBJECTIVE: Lung cancer is one of the unsafe diseases for human which reduces the patient life time. Generally, most of the lung cancers are identified after it has been spread into the lung parts and moreover it is difficult to find the lung cancer a...
Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy.
Radiation oncology (London, England)
Feb 23, 2022
BACKGROUND: In infrared reflective (IR) marker-based hybrid real-time tumor tracking (RTTT), the internal target position is predicted with the positions of IR markers attached on the patient's body surface using a prediction model. In this work, we ...
A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 21, 2022
Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, failure to adjust for SBDoH factors will potentially cause confounding i...
On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 21, 2022
Early detection and mitigation of disease recurrence in non-small cell lung cancer (NSCLC) patients is a nontrivial problem that is typically addressed either by rather generic follow-up screening guidelines, self-reporting, simple nomograms, or by m...
Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 18, 2022
BACKGROUND AND PURPOSE: To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, for predicting weekly anatomical changes of lung tumor and esophagus during definitive radiotherapy, incorporate the potential tumor shrinkage into a ...
A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging.
Biomedical physics & engineering express
Feb 18, 2022
Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for computer-aided diagnosis has received increasing attention. Supervised deep learning architectures are usually employed for the detection of abnormalities,...
Open, Video- and Robot-Assisted Thoracoscopic Lobectomy for Stage II-IIIA Non-Small Cell Lung Cancer.
The Annals of thoracic surgery
Feb 8, 2022
BACKGROUND: This study compares the short- and long-term outcomes of open vs robotic vs video-assisted thoracoscopic surgery (VATS) lobectomy for stage II-IIIA non-small-cell lung cancer (NSCLC).
Development of Deep Learning-based Automatic Scan Range Setting Model for Lung Cancer Screening Low-dose CT Imaging.
Academic radiology
Feb 5, 2022
RATIONALE AND OBJECTIVES: To develop an automatic setting of a deep learning-based system for detecting low-dose computed tomography (CT) lung cancer screening scan range and compare its efficiency with the radiographer's performance.
Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.
Journal of neuro-oncology
Feb 4, 2022
PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of NSCLCs harbor an activating mutation in the epidermal growth-factor receptor (EGFR), which may be targeted with selective EGFR inhibitors. However, d...
Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.
Scientific reports
Feb 3, 2022
Identifying the lung carcinoma subtype in small biopsy specimens is an important part of determining a suitable treatment plan but is often challenging without the help of special and/or immunohistochemical stains. Pathology image analysis that tackl...
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