AIMC Topic: Software

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Prediction of peptide hormones using an ensemble of machine learning and similarity-based methods.

Proteomics
Peptide hormones serve as genome-encoded signal transduction molecules that play essential roles in multicellular organisms, and their dysregulation can lead to various health problems. In this study, we propose a method for predicting hormonal pepti...

Leveraging artificial intelligence and software engineering methods in epidemiology for the co-creation of decision-support tools based on mechanistic models.

Preventive veterinary medicine
Epidemiological modeling is a key lever for infectious disease control and prevention on farms. It makes it possible to understand the spread of pathogens, but also to compare intervention scenarios even in counterfactual situations. However, the act...

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip.

Nature communications
By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms t...

Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives.

Current opinion in structural biology
New high-performance computing architectures are becoming operative, in addition to exascale computers. Quantum computers (QC) solve optimization problems with unprecedented efficiency and speed, while neuromorphic hardware (NMH) simulates neural net...

3DVascNet: An Automated Software for Segmentation and Quantification of Mouse Vascular Networks in 3D.

Arteriosclerosis, thrombosis, and vascular biology
BACKGROUND: Analysis of vascular networks is an essential step to unravel the mechanisms regulating the physiological and pathological organization of blood vessels. So far, most of the analyses are performed using 2-dimensional projections of 3-dime...

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans.

Scientific reports
In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast head computed tomography (CT) images. In total, 152 adult head CT sca...

The innovation of AI-based software in oral diseases: clinical-histopathological correlation diagnostic accuracy primary study.

BMC oral health
BACKGROUND: Machine learning (ML) through artificial intelligence (AI) could provide clinicians and oral pathologists to advance diagnostic problems in the field of potentially malignant lesions, oral cancer, periodontal diseases, salivary gland dise...

Svetlana a supervised segmentation classifier for Napari.

Scientific reports
We present Svetlana (SuperVised sEgmenTation cLAssifier for NapAri), an open-source Napari plugin dedicated to the manual or automatic classification of segmentation results. A few recent software tools have made it possible to automatically segment ...

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Neuroinformatics
Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in...

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

European radiology experimental
BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).