AIMC Topic: Workflow

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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...

DPDispatcher: Scalable HPC Task Scheduling for AI-Driven Science.

Journal of chemical information and modeling
Artificial intelligence (AI) is reshaping computational science, but AI-driven workflows routinely span heterogeneous tasks executed across diverse high-performance computing (HPC) systems. We introduce DPDispatcher, an open-source Python framework f...

A comparison of the performance of Chinese large language models and ChatGPT throughout the entire clinical workflow.

Scientific reports
BACKGROUND: ChatGPT has demonstrated strong performance in the complex, full clinical workflow. In recent years, several large language models (LLMs) from China have been introduced; however, their performance in such intricate tasks has yet to be th...

FragOPT: An ML-Driven Computational Workflow for Rational Fragments Optimization Toward Lead Compounds.

Journal of chemical information and modeling
Advances in machine learning (ML) offer significant potential to accelerate drug discovery. Although mathematical modeling and ML have become crucial in predicting drug-target interactions and properties, the complexity of chemical space and the "bla...

Development of a Smartphone-Based Inventory Management System for Emergency Carts.

Journal of medical systems
Inventory management for emergency carts is one of the routine tasks in hospitals. It is highly desirable to simplify the workflow of the inventory task since healthcare staffs always work under high pressure and heavy workload. In this study, we exp...

Single-cell RNA-sequencing of circulating tumour cells: A practical guide to workflow and translational applications.

Cancer metastasis reviews
The global burden of cancer is rising, with treatment failures often due to the metastatic nature of late-stage malignancies. Circulating tumour cells (CTCs) are metastatic precursors shed from primary tumours, which survive in circulation, extravasa...

A Deep Learning-Based Fully Automated Vertebra Segmentation and Labeling Workflow.

British journal of hospital medicine (London, England : 2005)
Spinal disorders, such as herniated discs and scoliosis, are highly prevalent conditions with rising incidence in the aging global population. Accurate analysis of spinal anatomical structures is a critical prerequisite for achieving high-precision ...

PyaiVS unifies AI workflows to accelerate ligand discovery and yields ABCG2 inhibitors.

European journal of medicinal chemistry
Developing optimized AI models for virtual screening requires coordinated selection of algorithms, molecular representations, and data splitting strategies, yet lacks integrated tools. We present PyaiVS, a Python package that integrates nine machine ...

Integrating Machine Learning into Free Energy Perturbation Workflows.

Journal of chemical information and modeling
Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein-ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup proc...

Deconvoluting and Interpreting Nontargeted Chemical Data: A Data-Driven Forensic Workflow for Identifying the Most Prominent Chemical Sources in Receiving Waters.

Environmental science & technology
Chemical forensics aims to identify major contamination sources, but existing workflows often rely on predefined targets and known sources, introducing bias. Here, we present a data-driven workflow that reduces this bias by applying an unsupervised m...