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Automation

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Benchmarking Automatic Speech Recognition Technology for Natural Language Samples of Children With and Without Developmental Delays.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Natural language sampling (NLS) offers rich insights into real-world speech and language usage across diverse groups; yet, human transcription is time-consuming and costly. Automatic speech recognition (ASR) technology has the potential to revolution...

An Automatic Method for Locating Positions and their Colors Important for Classifying Genders in Retinal Fundus Images by Deep Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper proposes an automatic method to identify important positions and their color features in retinal fundus images for gender classification using deep learning. The proposed method consists of MALCC (Model Analysis by Local Color Characterist...

Ultrasound for Automated Classification of Full-Thickness Rotator Cuff Tendon Tears using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Rotator cuff tendon tears, the most common shoulder injuries, are typically diagnosed mainly through MRI, but can also be seen on ultrasound (US), a much less costly test that currently requires highly-trained human expert operators. An AI tool to id...

Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The major challenge lies in manual segmentation of cells and quantifying cell size distribution is tediou...

Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses mac...

Advancing regenerative medicine: the Aceman system's pioneering automation and machine learning in mesenchymal stem cell biofabrication.

Biofabrication
Mesenchymal stem cells (MSCs) are pivotal in advancing regenerative medicine; however, the large-scale production of MSCs for clinical applications faces significant challenges related to efficiency, cost, and quality assurance. We introduce the Auto...

Automated Process for Monitoring of Amiodarone Treatment: Development and Evaluation.

Journal of medical Internet research
BACKGROUND: Amiodarone treatment requires repeated laboratory evaluations of thyroid and liver function due to potential side effects. Robotic process automation uses software robots to automate repetitive and routine tasks, and their use may be exte...

Enhancing automated right-sided early-stage breast cancer treatments via deep learning model adaptation without additional training.

Medical physics
BACKGROUND: Input data curation and model training are essential, but time-consuming steps in building a deep-learning (DL) auto-planning model, ensuring high-quality data and optimized performance. Ideally, one would prefer a DL model that exhibits ...

Automation bias in AI-assisted detection of cerebral aneurysms on time-of-flight MR angiography.

La Radiologia medica
PURPOSE: To determine how automation bias (inclination of humans to overly trust-automated decision-making systems) can affect radiologists when interpreting AI-detected cerebral aneurysm findings in time-of-flight magnetic resonance angiography (TOF...

WDRIV-Net: a weighted ensemble transfer learning to improve automatic type stratification of lumbar intervertebral disc bulge, prolapse, and herniation.

Biomedical engineering online
The degeneration of the intervertebral discs in the lumbar spine is the common cause of neurological and physical dysfunctions and chronic disability of patients, which can be stratified into single-(e.g., disc herniation, prolapse, or bulge) and com...