AIMC Topic: Automation

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Organic synthesis in a modular robotic system driven by a chemical programming language.

Science (New York, N.Y.)
The synthesis of complex organic compounds is largely a manual process that is often incompletely documented. To address these shortcomings, we developed an abstraction that maps commonly reported methodological instructions into discrete steps amena...

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.

Medical physics
PURPOSE: To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning-based three-dimensional (3D) dose prediction and a dose distribution-based plan generation algorith...

Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.

Medical physics
PURPOSE: Due to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it can effectively e...

Machine learning in population health: Opportunities and threats.

PLoS medicine
Abraham D. Flaxman and Theo Vos of the Institute for Health Metrics and Evaluation, University of Washington, discuss near-term applications for ML in population health and name their priorities for ongoing ML development.

Toward Automatic Risk Assessment to Support Suicide Prevention.

Crisis
Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide ri...

A feasibility study on an automated method to generate patient-specific dose distributions for radiotherapy using deep learning.

Medical physics
PURPOSE: To develop a method for predicting optimal dose distributions, given the planning image and segmented anatomy, by applying deep learning techniques to a database of previously optimized and approved Intensity-modulated radiation therapy trea...

Automated classification of benign and malignant lesions in F-NaF PET/CT images using machine learning.

Physics in medicine and biology
PURPOSE: F-NaF PET/CT imaging of bone metastases is confounded by tracer uptake in benign diseases, such as osteoarthritis. The goal of this work was to develop an automated bone lesion classification algorithm to classify lesions in NaF PET/CT image...