AIMC Topic: Automation

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A convolutional route to abbreviation disambiguation in clinical text.

Journal of biomedical informatics
OBJECTIVE: Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we ass...

Automated prediction of dosimetric eligibility of patients with prostate cancer undergoing intensity-modulated radiation therapy using a convolutional neural network.

Radiological physics and technology
The quality of radiotherapy has greatly improved due to the high precision achieved by intensity-modulated radiation therapy (IMRT). Studies have been conducted to increase the quality of planning and reduce the costs associated with planning through...

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Nature medicine
Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'. Although these disorders are often recognizabl...

Prognostication and Risk Factors for Cystic Fibrosis via Automated Machine Learning.

Scientific reports
Accurate prediction of survival for cystic fibrosis (CF) patients is instrumental in establishing the optimal timing for referring patients with terminal respiratory failure for lung transplantation (LT). Current practice considers referring patients...

Automation of the Differential Digestion Process of Sexual Assault Evidence.

Journal of forensic sciences
Sexual assault evidence samples require the use of a specific process known as a differential digestion to separate sperm from nonsperm cells prior to DNA extraction. An automated differential digestion process was developed using a selective degrada...

Segmentation of glandular epithelium in colorectal tumours to automatically compartmentalise IHC biomarker quantification: A deep learning approach.

Medical image analysis
In this paper, we propose a method for automatically annotating slide images from colorectal tissue samples. Our objective is to segment glandular epithelium in histological images from tissue slides submitted to different staining techniques, includ...

Automatic Annotation for Human Activity Recognition in Free Living Using a Smartphone.

Sensors (Basel, Switzerland)
Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, espec...

Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.

Echocardiography (Mount Kisco, N.Y.)
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to impro...

Automatic hand phantom map generation and detection using decomposition support vector machines.

Biomedical engineering online
BACKGROUND: There is a need for providing sensory feedback for myoelectric prosthesis users. Providing tactile feedback can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom lim...