AIMC Topic: Software

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Deep integration of low-cost liquid handling robots in an industrial pharmaceutical development environment.

SLAS technology
The pharmaceutical industry is increasingly embracing laboratory automation to enhance experimental efficiency and operational resilience, particularly through the integration of automated liquid handlers (ALHs). This paper explores the integration o...

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing.

Journal of medical imaging and radiation sciences
BACKGROUND: The reproducibility crisis in AI research remains a significant concern. While code sharing has been acknowledged as a step toward addressing this issue, our focus extends beyond this paradigm. In this work, we explore "federated testing"...

Retrospective validation study of a machine learning-based software for empirical and organism-targeted antibiotic therapy selection.

Antimicrobial agents and chemotherapy
UNLABELLED: Errors in antibiotic prescriptions are frequent, often resulting from the inadequate coverage of the infection-causative microorganism. The efficacy of iAST, a machine-learning-based software offering empirical and organism-targeted antib...

NeuroQuantify - An image analysis software for detection and quantification of neuron cells and neurite lengths using deep learning.

Journal of neuroscience methods
BACKGROUND: The segmentation of cells and neurites in microscopy images of neuronal networks provides valuable quantitative information about neuron growth and neuronal differentiation, including the number of cells, neurites, neurite length and neur...

Rapid discrimination between deleterious and benign missense mutations in the CAGI 6 experiment.

Human genomics
We describe the machine learning tool that we applied in the CAGI 6 experiment to predict whether single residue mutations in proteins are deleterious or benign. This tool was trained using only single sequences, i.e., without multiple sequence align...

Smart Classrooms: How Sensors and AI Are Shaping Educational Paradigms.

Sensors (Basel, Switzerland)
The integration of advanced technologies is revolutionizing classrooms, significantly enhancing their intelligence, interactivity, and personalization. Central to this transformation are sensor technologies, which play pivotal roles. While numerous s...

Smccnet 2.0: a comprehensive tool for multi-omics network inference with shiny visualization.

BMC bioinformatics
Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are speci...

aiSEGcell: User-friendly deep learning-based segmentation of nuclei in transmitted light images.

PLoS computational biology
Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminate...

ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) is revolutionizing Magnetic Resonance Imaging (MRI) along the acquisition and processing chain. Advanced AI frameworks have been applied in various successive tasks, such as image reconstruction...

PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides.

PloS one
Interleukin (IL)-13 has emerged as one of the recently identified cytokine. Since IL-13 causes the severity of COVID-19 and alters crucial biological processes, it is urgent to explore novel molecules or peptides capable of including IL-13. Computati...