AIMC Topic: Lung Neoplasms
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[Deep Learning-driven Pulmonary Nodule Detection from CT Images: Challenges, Current Status and Future Directions].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Feb 8, 2023
Automatic detection of pulmonary nodule based on CT images can significantly improve the diagnosis and treatment of lung cancer. Based on the characteristics of CT image and pulmonary nodule, this study summarizes the challenges and recent progresses...
Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.
Korean journal of radiology
Feb 1, 2023
OBJECTIVE: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the conc...
Complex Robotic Lung Resection.
Thoracic surgery clinics
Feb 1, 2023
Performing robotic thoracic lung resection is becoming an option for patients with complex thoracic disease. The robotic-assisted approach has similar survival with decreased postoperative pain, morbidity, and hospital length of stay compared with th...
Biportal robotic pulmonary lobectomy, initial experience - case report.
Rozhledy v chirurgii : mesicnik Ceskoslovenske chirurgicke spolecnosti
Jan 1, 2023
INTRODUCTION: Thanks to perfect visualization and high maneuverability of instruments, the robotic technique is a preferable type of lung resection, even though the number of required incisions is usually higher compared to the video-assisted approac...
Deep learning classifiers for computer-aided diagnosis of multiple lungs disease.
Journal of X-ray science and technology
Jan 1, 2023
BACKGROUND: Computer aided diagnosis has gained momentum in the recent past. The advances in deep learning and availability of huge volumes of data along with increased computational capabilities has reshaped the diagnosis and prognosis procedures.
Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture.
Journal of cancer research and therapeutics
Jan 1, 2023
AIM: Current radiotherapy treatment techniques require a large amount of imaging data for treatment planning which demand significant clinician's time to segment target volume and organs at risk (OARs). In this study, we propose to use U-net-based ar...
Prescreening in oncology trials using medical records. Natural language processing applied on lung cancer multidisciplinary team meeting reports.
Health informatics journal
Jan 1, 2023
Defining profiles of patients that could benefit from relevant anti-cancer treatments is essential. An increasing number of specific criteria are necessary to be eligible to specific anti-cancer therapies. This study aimed to develop an automated alg...
Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...
[Robot-assisted Segmentectomy for Lung Cancer].
Kyobu geka. The Japanese journal of thoracic surgery
Jan 1, 2023
The role of segmentectomy for lung cancer is expected to increase owing to the results of Japan Clinical Oncology Group (JCOG) 0802. Moreover, the major advantage of robot-assisted thoracic surgery (RATS) is that it allows high precision of dissectio...
[Introduction of Robot-assisted Lung Segmentectomy].
Kyobu geka. The Japanese journal of thoracic surgery
Jan 1, 2023
Robot-assisted lung segmentectomy will be covered by insurance starting 2020. The results of the Japan Clinical Oncology Group( JCOG) 0802 trial have been reported, and the use of robot-assisted lung segmentectomy is expected to increase in the futur...
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