AIMC Topic: Retrospective Studies

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Clinical efficacy of robot-assisted subxiphoid versus lateral thoracic approach in the treatment of anterior mediastinal tumors.

World journal of surgical oncology
BACKGROUND: The purpose of this study was to compare the perioperative efficacy and safety of da Vinci robot-assisted thoracoscopic surgery (RATS) for treating anterior mediastinal tumors through the subxiphoid and lateral thoracic approaches under t...

Differentiating malignant and benign eyelid lesions using deep learning.

Scientific reports
Artificial intelligence as a screening tool for eyelid lesions will be helpful for early diagnosis of eyelid malignancies and proper decision-making. This study aimed to evaluate the performance of a deep learning model in differentiating eyelid lesi...

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

PloS one
Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. H...

The effect of soft palate reconstruction with the da Vinci robot on middle ear function in children: an observational study.

International journal of oral and maxillofacial surgery
Cleft palate is associated with a high prevalence of middle ear dysfunction, even after palatal repair. The aim of this study was to evaluate the effects of robot-enhanced soft palate closure on middle ear functioning. This retrospective study compar...

Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.

European radiology
OBJECTIVES: This study aimed to investigate whether a deep learning (DL) model based on preoperative MR images of primary tumors can predict lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer.

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in pat...

Robot-assisted general surgery is safe during the learning curve: a 5-year Australian experience.

Journal of robotic surgery
Robot-assisted general surgery has become increasingly common in the Australian public sector since 2003. It provides significant technical advantages compared to laparoscopic surgery. Currently, it is estimated that the learning curve for surgeons s...

A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children.

Journal of digital imaging
Chest radiography is the modality of choice for the identification of rib fractures in young children and there is value for the development of computer-aided rib fracture detection in this age group. However, the automated identification of rib frac...

Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs.

PloS one
PURPOSE: Detection of early lung cancer using chest radiograph remains challenging. We aimed to highlight the benefit of using artificial intelligence (AI) in chest radiograph with regard to its role in the unexpected detection of resectable early lu...

Combination Use of Compressed Sensing and Deep Learning for Shoulder Magnetic Resonance Imaging With Various Sequences.

Journal of computer assisted tomography
OBJECTIVE: For compressed sensing (CS) to become widely used in routine magnetic resonance imaging (MRI), it is essential to improve image quality. This study aimed to evaluate the usefulness of combining CS and deep learning-based reconstruction (DL...