AIMC Topic: Retrospective Studies

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Performance of Biopsy Tools in Procurement of Lung Tissue in Robot-Assisted Peripheral Navigation: A Comparison.

Respiration; international review of thoracic diseases
INTRODUCTION: Robot-assisted navigation bronchoscopy (RANB) has been gaining traction as a new technology for minimally invasive biopsies of peripheral pulmonary lesions (PPLs). Cryobiopsy is an established method of procuring satisfactory lung tissu...

Use of deep learning model for paediatric elbow radiograph binomial classification: initial experience, performance and lessons learnt.

Singapore medical journal
INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency dep...

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.

Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms.

Journal of hepatology
BACKGROUND & AIMS: The Banff Liver Working Group recently published consensus recommendations for steatosis assessment in donor liver biopsy, but few studies reported their use and no automated deep-learning algorithms based on the proposed criteria ...

Machine learning models for early prediction of mortality risk in patients with burns: A single center experience.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Mortality rate is considered as the most important outcome measure for assessing the severity of burn injury. A scale or model that accurately predicts burn mortality can be useful to determine the clinical course of burn injuries, discuss treatment ...

Comparison of the efficacy and safety of single-port versus multi-port robotic total mesorectal excision for rectal cancer: A propensity score-matched analysis.

Surgery
BACKGROUND: It is unknown whether the da Vinci single-port system performs similarly to the previous multi-port system during complicated procedures, such as rectal cancer surgery. Therefore, we compared the short-term clinical outcomes of single-por...

Effect of da Vinci robot versus thoracoscopic surgery on lung function and oxidative stress levels in NSCLC patients: a propensity score-matched study.

Surgical endoscopy
BACKGROUND: To evaluate the short-term efficacy, lung function, and oxidative stress levels between the robotic-assisted thoracoscopic surgery (RATS) and video-assisted thoracoscopic surgery group (VATS) for non-small cell lung cancer (NSCLC).

Assessment of inspiration and technical quality in anteroposterior thoracic radiographs using machine learning.

Radiography (London, England : 1995)
INTRODUCTION: Chest radiographs are the most performed radiographic procedure, but suboptimal technical factors can impact clinical interpretation. A deep learning model was developed to assess technical and inspiratory adequacy of anteroposterior ch...

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach.

Scientific reports
Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers ...

Deep learning-based multi-stage postoperative type-b aortic dissection segmentation using global-local fusion learning.

Physics in medicine and biology
Type-b aortic dissection (AD) is a life-threatening cardiovascular disease and the primary treatment is thoracic endovascular aortic repair (TEVAR). Due to the lack of a rapid and accurate segmentation technique, the patient-specific postoperative AD...