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Does type of robotic platform make a difference in the final cost of robotic-assisted radical prostatectomy?

Journal of robotic surgery
This study evaluates the difference of robot-assisted radical prostatectomy (RARP) costs in patients with similar preoperative characteristics operated on using the da Vinci SP and Xi robotic platforms. We performed a retrospective analysis on 71 con...

Using deep learning models to analyze the cerebral edema complication caused by radiotherapy in patients with intracranial tumor.

Scientific reports
Using deep learning models to analyze patients with intracranial tumors, to study the image segmentation and standard results by clinical depiction complications of cerebral edema after receiving radiotherapy. In this study, patients with intracrania...

Age Classification in Forensic Medicine Using Machine Learning Techniques.

Sovremennye tekhnologii v meditsine
UNLABELLED: was to assess the capabilities of age determination (age group) at death using classification techniques by histomorphometric characteristics of osseous and cartilaginous tissue aging.

The Role of Decision Authority and Stated Social Intent as Predictors of Trust in Autonomous Robots.

Topics in cognitive science
Prior research has demonstrated that trust in robots and performance of robots are two important factors that influence human-autonomy teaming. However, other factors may influence users' perceptions and use of autonomous systems, such as perceived i...

Explainable artificial intelligence (XAI): closing the gap between image analysis and navigation in complex invasive diagnostic procedures.

World journal of urology
LITERATURE REVIEW: Cystoscopy is the gold standard for initial macroscopic assessments of the human urinary bladder to rule out (or diagnose) bladder cancer (BCa). Despite having guidelines, cystoscopic findings are diverse and often challenging to c...

Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction.

Korean journal of radiology
OBJECTIVE: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images.

Investigating Simultaneity for Deep Learning-Enhanced Actual Ultra-Low-Dose Amyloid PET/MR Imaging.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Diagnostic-quality amyloid PET images can be created with deep learning using actual ultra-low-dose PET images and simultaneous structural MR imaging. Here, we investigated whether simultaneity is required; if not, MR imaging-...

Site-agnostic 3D dose distribution prediction with deep learning neural networks.

Medical physics
PURPOSE: Typically, the current dose prediction models are limited to small amounts of data and require retraining for a specific site, often leading to suboptimal performance. We propose a site-agnostic, three-dimensional dose distribution predictio...

Multiresolution residual deep neural network for improving pelvic CBCT image quality.

Medical physics
PURPOSE: Cone-beam computed tomography (CBCT) is frequently used for accurate image-guided radiation therapy. However, the poor CBCT image quality prevents its further clinical use. Thus, it is important to improve the HU accuracy and structure prese...

A Preliminary Study on Realizing Human-Robot Mental Comforting Dialogue via Sharing Experience Emotionally.

Sensors (Basel, Switzerland)
Mental health issues are receiving more and more attention in society. In this paper, we introduce a preliminary study on human-robot mental comforting conversation, to make an android robot (ERICA) present an understanding of the user's situation by...