AIMC Topic: Automation

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A parallel network utilizing local features and global representations for segmentation of surgical instruments.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic image segmentation of surgical instruments is a fundamental task in robot-assisted minimally invasive surgery, which greatly improves the context awareness of surgeons during the operation. A novel method based on Mask R-CNN is pro...

Facilitating clinical research through automation: Combining optical character recognition with natural language processing.

Clinical trials (London, England)
BACKGROUND/AIMS: Performance status is crucial for most clinical research, as an eligibility criterion, a comorbidity covariate, or a trial endpoint. Yet information on performance status often is embedded as free text within a patient's electronic m...

Automated Drug Coding Using Artificial Intelligence: An Evaluation of WHODrug Koda on Adverse Event Reports.

Drug safety
INTRODUCTION: Coding medicinal products described on adverse event (AE) reports to specific entries in standardised drug dictionaries, such as WHODrug Global, is a time-consuming step in case processing activities despite its potential for automation...

Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance.

Drug safety
TransCelerate reports on the results of 2019, 2020, and 2021 member company (MC) surveys on the use of intelligent automation in pharmacovigilance processes. MCs increased the number and extent of implementation of intelligent automation solutions th...

LAP: Latency-aware automated pruning with dynamic-based filter selection.

Neural networks : the official journal of the International Neural Network Society
Model pruning is widely used to compress and accelerate convolutional neural networks (CNNs). Conventional pruning techniques only focus on how to remove more parameters while ensuring model accuracy. This work not only covers the optimization of mod...

ResNet-50 for 12-Lead Electrocardiogram Automated Diagnosis.

Computational intelligence and neuroscience
Nowadays, the implementation of Artificial Intelligence (AI) in medical diagnosis has attracted major attention within both the academic literature and industrial sector. AI would include deep learning (DL) models, where these models have been achiev...

The Effect of the MFCC Frame Length in Automatic Voice Pathology Detection.

Journal of voice : official journal of the Voice Foundation
Automatic voice pathology detection is a research topic, which has gained increasing interest recently. Although methods based on deep learning are becoming popular, the classical pipeline systems based on a two-stage architecture consisting of a fea...

[Automation and application of robotics in the pathology laboratory].

Der Pathologe
Over the last 20 years, numerous technical innovations have been introduced to the histopathology laboratory, providing tools for improved standardization and occupational safety. Digital tracking serves as a backbone accompanying the workflow from l...

Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) technologies have resulted in remarkable achievements and conferred massive benefits to computer-aided systems in medical imaging. However, the worldwide usage of AI-based automation-assisted cervical cancer screening sys...

How to compete with robots by assessing job automation risks and resilient alternatives.

Science robotics
The effects of robotics and artificial intelligence (AI) on the job market are matters of great social concern. Economists and technology experts are debating at what rate, and to what extent, technology could be used to replace humans in occupations...