AIMC Topic: Humans

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Comparison of the operative outcomes and learning curves between laparoscopic and "Micro Hand S" robot-assisted total mesorectal excision for rectal cancer: a retrospective study.

BMC gastroenterology
BACKGROUND: The Micro Hand S robot is a new surgical tool that has been applied to total mesorectal excision (TME) surgery for rectal cancer in our center. In this study, we compared the operative outcomes, functional outcomes and learning curves of ...

Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.

BMC medical imaging
BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measu...

Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

New Challenges for Ethics: The Social Impact of Posthumanism, Robots, and Artificial Intelligence.

Journal of healthcare engineering
The ethical approach to science and technology is based on their use and application in extremely diverse fields. Less prominence has been given to the theme of the profound changes in our conception of human nature produced by the most recent develo...

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

PloS one
Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrained environments, and a computer-aided detection system (CAD) that can identify pneumonia on CXR may help the triage of patients in those environment ...

Weakly Supervised Deep Learning Approach to Breast MRI Assessment.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate a weakly supervised deep learning approach to breast Magnetic Resonance Imaging (MRI) assessment without pixel level segmentation in order to improve the specificity of breast MRI lesion classification.

MHSU-Net: A more versatile neural network for medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Medical image segmentation plays an important role in clinic. Recently, with the development of deep learning, many convolutional neural network (CNN)-based medical image segmentation algorithms have been proposed. Among the...

Outcomes of robotic coronary artery bypass versus nonrobotic coronary artery bypass.

Journal of cardiac surgery
BACKGROUND: Robotic coronary artery bypass graft (CABG) has developed in recent decades, however, prior studies showed conflicting result of robotic CABG compared to nonrobotic CABG in terms of mortality, morbidity, and cost. Herein, we sought to ana...

Commentary: When will the robots come marching in?

Journal of cardiac surgery
Minimally invasive techniques for coronary artery bypass grafting (CABG), specifically robotic-assisted CABG has increased in popularity despite conflicting evidence. Here, we review a report by Yokoyama and colleagues to the Journal of Cardiac Surge...

Predicting cell behaviour parameters from glioblastoma on a chip images. A deep learning approach.

Computers in biology and medicine
The broad possibilities offered by microfluidic devices in relation to massive data monitoring and acquisition open the door to the use of deep learning technologies in a very promising field: cell culture monitoring. In this work, we develop a metho...