AI Medical Compendium Topic:
Prospective Studies

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Prospective assessment of pancreatic ductal adenocarcinoma diagnosis from endoscopic ultrasonography images with the assistance of deep learning.

Cancer
BACKGROUND: Endosonographers are highly dependent on the diagnosis of pancreatic ductal adenocarcinoma (PDAC). The objectives of this study were to develop a deep-learning radiomics (DLR) model based on endoscopic ultrasonography (EUS) images for ide...

Impact on the ability of healthcare professionals to correctly identify patient-ventilator asynchronies of the simultaneous visualization of estimated muscle pressure curves on the ventilator display: a randomized study (P study).

Critical care (London, England)
BACKGROUND: Patient-ventilator asynchronies are usually detected by visual inspection of ventilator waveforms but with low sensitivity, even when performed by experts in the field. Recently, estimation of the inspiratory muscle pressure (P) waveforms...

Robot-assisted and fluorescence-guided remnant-cholecystectomy: a prospective dual-center cohort study.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Abdominal symptoms after cholecystectomy may be caused by gallstones in a remnant gallbladder or a long cystic duct stump. Resection of a remnant gallbladder or cystic duct stump is associated with an increased risk of conversion and bile...

Assessment of artificial intelligence-based remote monitoring of clear aligner therapy: A prospective study.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Artificial intelligence remote monitoring of clear aligner therapy has recently gained popularity. It uses deep learning algorithms on a patient's mobile smartphone to determine readiness to progress to the next aligner (ie, GO vs NO-GO...

Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

European radiology
OBJECTIVES: To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V...

Initial Experience of Robot-Assisted Partial Nephrectomy Using Hinotori Surgical Robot System: Single Institutional Prospective Assessment of Perioperative Outcomes in 30 Cases.

Journal of endourology
Innovation of robotic surgery is still actively growing, and various novel robotic systems are in the process of development. The objective of this study was to assess the perioperative outcomes of robot-assisted partial nephrectomy (RAPN) using the...

An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.

Reproductive biomedicine online
RESEARCH QUESTION: Can a multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical parameters provide personalized evaluation of endometrial receptivity and predict the occurrence of clinical pregnancy after fr...

Robot-assisted lateral pelvic lymph node dissection in patients with advanced rectal cancer: a single-center experience of 65 cases.

Journal of robotic surgery
The treatment of lateral pelvic lymph node (LPLN) metastasis of rectal cancer has evolved because of technical difficulties from open surgery to laparoscopy and, recently, robot-assisted surgery. This study aimed to evaluate the technical feasibility...

Teaching robotic cystectomy: prospective pilot clinical validation of the ERUS training curriculum.

BJU international
OBJECTIVE: To provide the first clinical validation of the European Association of Urology Robotic Urology Section (ERUS) curriculum for training in robot-assisted radical cystectomy with intracorporeal urinary diversion (iRARC).

Deep learning-based recognition of key anatomical structures during robot-assisted minimally invasive esophagectomy.

Surgical endoscopy
OBJECTIVE: To develop a deep learning algorithm for anatomy recognition in thoracoscopic video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures using deep learning.