AIMC Topic: Humans

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Comparison of machine learning classification techniques to predict implantation success in an IVF treatment cycle.

Reproductive biomedicine online
RESEARCH QUESTION: Which machine learning model predicts the implantation outcome better in an IVF cycle? What is the importance of each variable in predicting the implantation outcome in an IVF cycle?

The new surgical robotic platform HUGO RAS: System description and docking settings for robot-assisted radical prostatectomy.

Urologia
BACKGROUND: To date, robotic surgery in urology is well established all over the world. The newest platform on the market is the HUGO™ RAS system, developed by Medtronic. In this paper we provide a brief description of the system and describe our sys...

Robot-assisted anterior resection for rectal cancer with double inferior vena cava: A case report.

Asian journal of endoscopic surgery
Double inferior vena cava (DIVC) is a rare but generally asymptomatic condition that is often detected incidentally by radiological examinations such as computed tomography (CT). Here, we describe the case of a 73-year-old woman with DIVC, who underw...

Robot-assisted versus conventional laparoscopic partial nephrectomy for renal hilar tumors: Parenchymal preservation and functional recovery.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVE: To determine whether robot-assisted laparoscopic partial nephrectomy (RALPN) can benefit patients in terms of functional recovery in the treatment of renal hilar tumors compared to conventional laparoscopic partial nephrectomy (CLPN).

Automated Surgical-Phase Recognition for Robot-Assisted Minimally Invasive Esophagectomy Using Artificial Intelligence.

Annals of surgical oncology
BACKGROUND: Although a number of robot-assisted minimally invasive esophagectomy (RAMIE) procedures have been performed due to three-dimensional field of view, image stabilization, and flexible joint function, both the surgeons and surgical teams req...

Deep Learning-based Post Hoc CT Denoising for Myocardial Delayed Enhancement.

Radiology
Background To improve myocardial delayed enhancement (MDE) CT, a deep learning (DL)-based post hoc denoising method supervised with averaged MDE CT data was developed. Purpose To assess the image quality of denoised MDE CT images and evaluate their d...

Use of deep learning to predict postoperative recurrence of lung adenocarcinoma from preoperative CT.

International journal of computer assisted radiology and surgery
PURPOSE: Although surgery is the primary treatment for lung cancer, some patients experience recurrence at a certain rate. If postoperative recurrence can be predicted early before treatment is initiated, it may be possible to provide individualized ...