AIMC Topic: Retrospective Studies

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Deep learning of endoscopic features for the assessment of neoadjuvant therapy response in locally advanced rectal cancer.

Asian journal of surgery
BACKGROUND: For locally advanced rectal cancer (LARC), accurate response evaluation is necessary to select complete responders after neoadjuvant therapy (NAT) for a watch-and-wait (W&W) strategy. Algorithms based on deep learning have shown great val...

Deep learning-based diagnosis of osteoblastic bone metastases and bone islands in computed tomograph images: a multicenter diagnostic study.

European radiology
OBJECTIVE: To develop and validate a deep learning (DL) model based on CT for differentiating bone islands and osteoblastic bone metastases.

Diagnostic Test Accuracy of Artificial Intelligence in Detecting Periapical Periodontitis on Two-Dimensional Radiographs: A Retrospective Study and Literature Review.

Medicina (Kaunas, Lithuania)
This study aims to evaluate the diagnostic accuracy of artificial intelligence in detecting apical pathosis on periapical radiographs. A total of twenty anonymized periapical radiographs were retrieved from the database of Poznan University of Medica...

Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.

European radiology
OBJECTIVES: To establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation.

Quality of life, voiding & sexual dysfunction following robot-assisted vesicovaginal fistula repair: a tertiary care centre experience.

Journal of robotic surgery
Robot-assisted VVF (RA-VVF) repair has the advantage of small cystotomy, precise dissection and minimal surrounding tissue trauma. Translation of this to better functional outcomes is not studied so far. This study aims to evaluate the quality of lif...

Identification of Origin for Spinal Metastases from MR Images: Comparison Between Radiomics and Deep Learning Methods.

World neurosurgery
OBJECTIVE: To determine whether spinal metastatic lesions originated from lung cancer or from other cancers based on spinal contrast-enhanced T1 (CET1) magnetic resonance (MR) images analyzed using radiomics (RAD) and deep learning (DL) methods.

The value of deep learning-based computer aided diagnostic system in improving diagnostic performance of rib fractures in acute blunt trauma.

BMC medical imaging
BACKGROUND: To evaluate the value of a deep learning-based computer-aided diagnostic system (DL-CAD) in improving the diagnostic performance of acute rib fractures in patients with chest trauma.

Outcomes of Robotic Simple Prostatectomy After Prior Failed Endoscopic Treatment of Benign Prostatic Hyperplasia.

Journal of endourology
We compared outcomes of robot-assisted simple prostatectomy (RASP) in patients with and without a history of prior prostate surgery for management of symptomatic benign prostatic hyperplasia (BPH). We retrospectively reviewed our multi-institutiona...

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma.

Hepatobiliary & pancreatic diseases international : HBPD INT
BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying...

Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). In ...