AIMC Topic: Software

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Human vs machine: identifying ChatGPT-generated abstracts in Gynecology and Urogynecology.

American journal of obstetrics and gynecology
BACKGROUND: ChatGPT, a publicly available artificial intelligence large language model, has allowed for sophisticated artificial intelligence technology on demand. Indeed, use of ChatGPT has already begun to make its way into medical research. Howeve...

Predictors of Disease Progression and Adverse Clinical Outcomes in Patients With Moderate Aortic Stenosis Using an Artificial Intelligence-Based Software Platform.

The American journal of cardiology
Patients with moderate aortic stenosis (AS) have a greater risk of adverse clinical outcomes than that of the general population. How this risk compares with those with severe AS, along with factors associated with outcomes and disease progression, i...

Protocol for creating representations of molecular structures using a polymer-specific decoder.

STAR protocols
To supply chemical structures of polymers for machine learning applications, decoding is necessary. Here, we present a protocol for generating polymer fingerprints (PFPs), which are representations of molecular structures, using a polymer-specific de...

The fine line between automation and augmentation in website usability evaluation.

Scientific reports
Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are mo...

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The transla...

UNNT: A novel Utility for comparing Neural Net and Tree-based models.

PLoS computational biology
The use of deep learning (DL) is steadily gaining traction in scientific challenges such as cancer research. Advances in enhanced data generation, machine learning algorithms, and compute infrastructure have led to an acceleration in the use of deep ...

KbhbXG: A Machine learning architecture based on XGBoost for prediction of lysine β-Hydroxybutyrylation (Kbhb) modification sites.

Methods (San Diego, Calif.)
Lysine β-hydroxybutyrylation is an important post-translational modification (PTM) involved in various physiological and biological processes. In this research, we introduce a novel predictor KbhbXG, which utilizes XGBoost to identify β-hydroxybutyry...

3D printing of an artificial intelligence-generated patient-specific coronary artery segmentation in a support bath.

Biomedical materials (Bristol, England)
Accurate segmentation of coronary artery tree and personalized 3D printing from medical images is essential for CAD diagnosis and treatment. The current literature on 3D printing relies solely on generic models created with different software or 3D c...

Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.

European journal of ophthalmology
To assess the role of artificial intelligence (AI) based automated software for detection of Diabetic Retinopathy (DR) compared with the evaluation of digital retinography by two double masked retina specialists. Two-hundred one patients (mean age ...

Exploiting protein language models for the precise classification of ion channels and ion transporters.

Proteins
This study introduces TooT-PLM-ionCT, a comprehensive framework that consolidates three distinct systems, each meticulously tailored for one of the following tasks: distinguishing ion channels (ICs) from membrane proteins (MPs), segregating ion trans...