AIMC Topic: Automation

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Automatic lung dose painting for functional lung avoidance radiotherapy through multi-modality-guided dose prediction.

Physics in medicine and biology
This study aims to develop a multi-modality-guided dose prediction (MMDP)-based auto-planning algorithm for functional lung avoidance radiotherapy (FLART) guided by voxel-wise lung function images.The proposed auto-planning algorithm consists of a no...

A physicochemically compatible ferrofluid droplet robotic system for automated bioanalytical assays.

Lab on a chip
Droplet robotics is an emerging area of research focused on harnessing externally programmable physical fields to drive liquid droplet motion and automate complex fluidic operations. One approach for driving droplet robotic systems utilizes magnetic ...

Automating Life Cycle Assessments through Artificial Intelligence Agents and Integrated Assessment Models.

Environmental science & technology
Life cycle assessments (LCA) are a critical decision support tool for environmentally sustainable decision-making, but barriers such as time and resource intensity inhibit widespread application of LCA. To overcome these challenges, LCAs have been pa...

OntoSecAI: Ontology-driven security automation for AI-enabled systems.

PloS one
The advent of artificial intelligence (AI) models presents significant opportunities alongside inherent security risks, such as the exploitation by adversaries generating malicious data to compromise other AI-enabled systems. Despite the urgent need ...

New insights into automatic treatment planning for cancer radiotherapy using explainable artificial intelligence.

Physics in medicine and biology
This study aims to uncover the opaque decision-making process of an artificial intelligence (AI) agent for automatic treatment planning.We examined a previously developed AI agent based on the actor-critic with experience replay (ACER) network, which...

Development and application of an artificial intelligence-assisted endoscopic system for automatic and accurate diagnosis of colorectal ulcers.

International journal of colorectal disease
OBJECTIVES: Crohn's disease (CD), ulcerative colitis (UC), intestinal Behçet's disease (BD), intestinal tuberculosis (ITB), and primary intestinal lymphoma (PIL) are major intestinal disorders that frequently present with mucosal ulceration. Accurate...

Leveraging Machine Learning and Robotic Process Automation to Identify and Convert Unstructured Colonoscopy Results Into Actionable Data: Proof-of-Concept Study.

JMIR medical informatics
BACKGROUND: With rising patient volumes and a focus on quality, our health system had the objective to create a more efficient way to ensure accurate documentation of colorectal cancer (CRC) screening intervals from inbound colonoscopy reports to ens...

AI-driven software for automated quantification of skeletal metastases and treatment response evaluation using whole-body diffusion-weighted MRI (WB-DWI) in advanced prostate cancer.

Physics in medicine and biology
. Quantitative assessment of treatment response in advanced prostate cancer (APC) with bone metastases remains an unmet clinical need. Whole-body diffusion-weighted MRI (WB-DWI) provides two response biomarkers: total diffusion volume (TDV) and globa...

Deep Learning for Automated Measures of SUV and Molecular Tumor Volume in [Ga]PSMA-11 or [F]DCFPyL, [F]FDG, and [Lu]Lu-PSMA-617 Imaging with Global Threshold Regional Consensus Network.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Metastatic castration-resistant prostate cancer has a high rate of mortality with a limited number of effective treatments after hormone therapy. Radiopharmaceutical therapy with [Lu]Lu-prostate-specific membrane antigen-617 (LuPSMA) is one treatment...

Fully Automated Image-Based Multiplexing of Serial PET/CT Imaging for Facilitating Comprehensive Disease Phenotyping.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Combined PET/CT imaging provides critical insights into both anatomic and molecular processes, yet traditional single-tracer approaches limit multidimensional disease phenotyping; to address this, we developed the PET Unified Multitracer Alignment (P...