AIMC Topic: Automation

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Smart Reaction Templating: A Graph-Based Method for Automated Molecular Dynamics Input Generation.

Journal of chemical information and modeling
Accurately modeling chemical reactions in molecular dynamics simulations requires detailed pre- and postreaction templates, often created through labor-intensive manual workflows. This work introduces a Python-based algorithm that automates the gener...

Automating the Analysis of Substrate Reactivity through Environment Interaction Mapping.

Journal of chemical information and modeling
Exploring the interaction configurations between substrates and atomic or molecular systems is crucial for various scientific and technological applications, such as characterizing catalytic reactions, solvation structures, and molecular interactions...

Pattern recognition in crash clusters involving vehicles with advanced driving technologies.

Accident; analysis and prevention
Autonomous Vehicle (AV) technologies, including Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS), have significant potential to reduce crashes caused by driver errors. However, as AVs become more prevalent on roadways, th...

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep learning (DL) in [F]FDG and [Ga]Ga-prostate-specific membrane antigen (PSMA) PET/CT scans. We used 489 ...

Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

The international journal of cardiovascular imaging
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...

The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses.

Biomedical engineering online
BACKGROUND: Chronic rhinosinusitis (CRS) is diagnosed with symptoms and objective endoscopy or computed tomography (CT). The Lund-Mackay score (LMS) is often used to determine the radiologic severity of CRS and make clinical decisions. This proof-of-...

Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging
Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart disease screening modality. However, its clinical application is hindered by inherent limitations, including low spatial resolution and insufficient co...

Reinforcement learning-driven automated head and neck simultaneous integrated boost (SIB) radiation therapy: flexible treatment planning aligned with clinical preferences.

Physics in medicine and biology
Head-and-neck simultaneous integrated boost (SIB) treatment planning using intensity modulated radiation therapy is particularly challenging due to the proximity to organs-at-risk. Depending on the specific clinical conditions, different parotid-spar...

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida.

Communications biology
Although synthetic biology can produce valuable chemicals in a renewable manner, its progress is still hindered by a lack of predictive capabilities. Media optimization is a critical, and often overlooked, process which is essential to obtain the tit...