AIMC Topic: Workflow

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Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.

Journal of neurointerventional surgery
BACKGROUND: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction a...

A Framework for a Standard-Enabled FAIR Data Management Workflow for Synthetic Biology.

ACS synthetic biology
Synthetic biology laboratories generate diverse forms of data and metadata throughout a project's life cycle, such as sequences, models, protocols, images, and time-series measurements. Unfortunately, these assets are scattered across spreadsheets, p...

The Current State of Digital Scribes in Primary Care: A Scoping Review.

Journal of medical systems
The purpose of this scoping review is to explore the current state of digital scribe technology in primary care, focusing on how automatic speech recognition (ASR) and natural language processing (NLP), which are foundational technologies behind arti...

Measuring provider-level differences in perioperative workflow using computer vision-based artificial intelligence.

BMJ health & care informatics
OBJECTIVES: To evaluate provider-level variability across the full perioperative workflow using a computer vision-based artificial intelligence (AI) system that automatically detects and timestamps operating room events.

Deep learning-based autonomous retinal vein cannulation in ex vivo porcine eyes.

Science robotics
Retinal vein cannulation (RVC) is an emerging method for treating retinal vein occlusion (RVO). The success of this procedure depends on surgeon expertise and, recently, robotic assistance. This paper proposes an autonomous RVC workflow leveraging de...

Hype vs Reality in the Integration of Artificial Intelligence in Clinical Workflows.

JMIR formative research
Artificial intelligence (AI) has the capacity to transform health care by improving clinical decision-making, optimizing workflows, and enhancing patient outcomes. However, this potential remains limited by a complex set of technological, human, and ...

Machine Learning-Assisted False Positive Detection in Metabolite Identification Workflows.

Analytical chemistry
Metabolite identification is a pivotal step in drug discovery and development, enabling the comprehensive analysis of drug-derived compounds within biological systems. However, the complexity of liquid chromatography-mass spectrometry data often resu...

Trends and Trajectories in the Rise of Large Language Models in Radiology: Scoping Review.

JMIR medical informatics
BACKGROUND: The use of large language models (LLMs) in radiology is expanding rapidly, offering new possibilities in report generation, decision support, and workflow optimization. However, a comprehensive evaluation of their applications, performanc...

SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis.

Nature communications
Multiplexed imaging has transformed our ability to study tissue organization by capturing thousands of cells and molecules in their native context. However, these datasets are enormous, often comprising tens of gigabytes per image, and require comple...

AUPA: weakly supervised approach for streamlining breast cancer diagnostic workflow by WSI histological type classification for efficient IHC triage.

Scientific reports
In routine breast cancer diagnostics, pathologists often review each case twice-first to determine the need for immunohistochemical (IHC) stains, and a second time to issue the final diagnosis-creating significant workload and delays. We present an a...