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Introducing AnatomyGPT: A customized artificial intelligence application for anatomical sciences education.

Clinical anatomy (New York, N.Y.)
Artificial intelligence (AI) technologies are poised to become an increasingly important part of education in the anatomical sciences. OpenAI has also introduced generative pretrained transformers (GPTs), which are customizable versions of the standa...

CancerGATE: Prediction of cancer-driver genes using graph attention autoencoders.

Computers in biology and medicine
Discovery of the cancer type specific-driver genes is important for understanding the molecular mechanisms of each cancer type and for providing proper treatment. Recently, graph deep learning methods became widely used in finding cancer-driver genes...

Accurate structure prediction of biomolecular interactions with AlphaFold 3.

Nature
The introduction of AlphaFold 2 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design. Here we describe our AlphaFold 3 model with a substantially...

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...