OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...
PURPOSE: We sought to automate R.E.N.A.L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry scoring of preoperative computerized tomography scans and create an ...
BMC medical informatics and decision making
Dec 30, 2021
BACKGROUND: For liver cancer patients, the occurrence of postoperative complications increases the difficulty of perioperative nursing, prolongs the hospitalization time of patients, and leads to large increases in hospitalization costs. The ability ...
Big data (BD) and artificial intelligence (AI) have increasingly been used in neurocritical care. "BD" can be operationally defined as extremely large datasets that are so large and complex that they cannot be analyzed by using traditional statistica...
Journal of laparoendoscopic & advanced surgical techniques. Part A
Dec 28, 2021
To evaluate the impact of body mass index (BMI), preoperative risk classification, previous inguinal herniotomy, and abdominal operations on several steps of robot-assisted radical prostatectomy (RARP) and lymph node (LN) involvement. A total numbe...
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...
AIM: The objective of the present study was to compare the outcomes of open versus laparoscopic versus robotic cystectomy and ileal conduit for neurogenic lower urinary tract dysfunction (NLUTD).
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 27, 2021
BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of colorectal cancer (CRC). Here, we established and validated a deep learning (DPL) model for predicting lymph node metastasis (LNM) in CRC.
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