AIMC Topic: Workflow

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Brain MR-only workflow in clinical practice: A comparison among generators for quality assurance and patient positioning.

Journal of applied clinical medical physics
BACKGROUND AND PURPOSE: Routine quality control procedures are still required for sCT based on artificial intelligence (AI) to verify the performance of the generators. The aim of this study was to evaluate three generators based on AI or bulk densit...

Implementation of Machine Learning Applications in Health Care Organizations: Systematic Review of Empirical Studies.

Journal of medical Internet research
BACKGROUND: There is a growing enthusiasm for machine learning (ML) among academics and health care practitioners. Despite the transformative potential of ML-based applications for patient care, their uptake and implementation in health care organiza...

The Transformative Impact of AI, Extended Reality, and Robotics in Interventional Radiology: Current Trends and Applications.

Techniques in vascular and interventional radiology
Interventional Radiology is at the forefront of integrating advanced imaging techniques and minimally-invasive procedures to enhance patient care. The advent of Digital Health Technologies (DHTs), including artificial intelligence (AI), robotics, and...

Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.

eLife
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study...

Automated Single Cell Phenotyping of Time-of-Flight Secondary Ion Mass Spectrometry Tissue Images.

Journal of the American Society for Mass Spectrometry
Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many diffe...

Autonomous mobile robots for exploratory synthetic chemistry.

Nature
Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making. Most autonomous laboratories involve bespoke automated equipment, and reaction outcomes are ofte...

Classifying driver mutations of papillary thyroid carcinoma on whole slide image: an automated workflow applying deep convolutional neural network.

Frontiers in endocrinology
BACKGROUND: Informative biomarkers play a vital role in guiding clinical decisions regarding management of cancers. We have previously demonstrated the potential of a deep convolutional neural network (CNN) for predicting cancer driver gene mutations...

Management of experimental workflows in robotic cultivation platforms.

SLAS technology
In the last decades, robotic cultivation facilities combined with automated execution of workflows have drastically increased the speed of research in biotechnology. In this work, we present the design and deployment of a digital infrastructure for r...

A machine learning-based workflow for predicting transplant outcomes in patients with sickle cell disease.

British journal of haematology
Allogeneic haematopoietic cell transplantation (HCT) with HLA-matched sibling donor remains the most established curative therapeutic option for patients with sickle cell disease (SCD). However, it is not without risks, highlighting the need for a ri...

Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.

Annals of vascular surgery
BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP meth...