AIMC Topic: Workflow

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[Automation and the use of robots in the pathology laboratory : A journey through time and a consideration of efficiency].

Pathologie (Heidelberg, Germany)
In the past 20 years, numerous technical innovations were introduced to the histopathology laboratory, providing tools for improved standardization and occupational safety. Digital tracking serves as a backbone accompanying the workflow from the labe...

Artificial intelligence workflow quantifying muscle features on Hematoxylin-Eosin stained sections reveals dystrophic phenotype amelioration upon treatment.

Scientific reports
Cell segmentation is a key step for a wide variety of biological investigations, especially in the context of muscle science. Currently, automated methods still struggle to perform skeletal muscle fiber quantification on Hematoxylin-Eosin (HE) staine...

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.

Scientific reports
Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challengi...

Advanced Control Systems in Industry 5.0 Enabling Process Mining.

Sensors (Basel, Switzerland)
This paper merges new research topics in Industry 5.0 using the Business Process Modeling and Notation (BPMN) approach able to integrate Artificial Intelligence (AI) in production processes. The goal is to provide an innovative approach to model prod...

A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.

Nature communications
This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the in...

Ontology-based surgical workflow recognition and prediction.

Journal of biomedical informatics
BACKGROUND: Surgical context-aware systems can adapt to the current situation in the operating room and thus provide computer-aided assistance functionalities and intraoperative decision-support. To interact with the surgical team perceptively and as...

Applying interpretable machine learning workflow to evaluate exposure-response relationships for large-molecule oncology drugs.

CPT: pharmacometrics & systems pharmacology
The application of logistic regression (LR) and Cox Proportional Hazard (CoxPH) models are well-established for evaluating exposure-response (E-R) relationship in large molecule oncology drugs. However, applying machine learning (ML) models on evalua...

Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks.

Molecules (Basel, Switzerland)
Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary stages. Drug repurposing is an important method that bypasses lengthy drug discovery procedures and focuses on discovering new usages for known medicati...

Adversarial attacks and adversarial robustness in computational pathology.

Nature communications
Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to q...

A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma.

Histopathology
AIMS: The reporting of tumour cellularity in cancer samples has become a mandatory task for pathologists. However, the estimation of tumour cellularity is often inaccurate. Therefore, we propose a collaborative workflow between pathologists and artif...