AIMC Topic: Workflow

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Systematic review on the impact of deep learning-driven worklist triage on radiology workflow and clinical outcomes.

European radiology
OBJECTIVES: To perform a systematic review on the impact of deep learning (DL)-based triage for reducing diagnostic delays and improving patient outcomes in peer-reviewed and pre-print publications.

Insights into radiomics: a comprehensive review for beginners.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Radiomics and artificial intelligence (AI) are rapidly evolving, significantly transforming the field of medical imaging. Despite their growing adoption, these technologies remain challenging to approach due to their technical complexity. This review...

Medical machine learning operations: a framework to facilitate clinical AI development and deployment in radiology.

European radiology
The integration of machine-learning technologies into radiology practice has the potential to significantly enhance diagnostic workflows and patient care. However, the successful deployment and maintenance of medical machine-learning (MedML) systems ...

Selecting high-throughput scanners for clinical use: A multicenter institution experience.

American journal of clinical pathology
OBJECTIVE: To evaluate and implement whole-slide imaging (WSI) scanners for a fully digital pathology workflow at the University Health Network (UHN) in Canada, a multicenter institution. The goal was to optimize clinical diagnosis, education, telepa...

Impact of a computed tomography-based artificial intelligence software on radiologists' workflow for detecting acute intracranial hemorrhage.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: To assess the impact of a commercially available computed tomography (CT)-based artificial intelligence (AI) software for detecting acute intracranial hemorrhage (AIH) on radiologists' diagnostic performance and workflow in a real-world clin...

Longitudinal evaluation of workflow optimization in radiotherapy: A 4-year retrospective study.

Journal of applied clinical medical physics
BACKGROUND: Efficient workflows are essential for timely, high-quality radiotherapy. In 2020, an internal audit identified key workflow bottlenecks, including long patient wait times, suboptimal treatment planning, and inadequate quality control. Acc...

Deep Learning Models Connecting Images and Text: A Primer for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc
In radiology practice, medical images are described and interpreted by radiologists in text reports. Recent technical developments enabling deep learning models to connect images and text may facilitate the radiologic workflow. These developments inc...

Metagenomics-Toolkit: the flexible and efficient cloud-based metagenomics workflow featuring machine learning-enabled resource allocation.

NAR genomics and bioinformatics
The metagenome analysis of complex environments with thousands of datasets, such as those in the Sequence Read Archive, requires substantial computational resources for it to be completed within a reasonable time frame. Efficient use of infrastructur...

Integration of Generative AI with Human Expertise in HEOR: A Hybrid Intelligence Framework.

Advances in therapy
INTRODUCTION: Health economics and outcomes research (HEOR) is pivotal in shaping healthcare policies, optimizing decision-making, and ensuring effective resource allocation. However, current HEOR workflows often struggle to keep pace with the growin...