Prescriptions

Research on early warning model of coal spontaneous combustion based on interpretability.

Predicting the temperature of the coal spontaneous combustion (CSC) is essential for preventing and managing coal mine fires. In this paper, a Rough Set-Stacking-SHapley Additive Explanations (RS-Stacking-SHAP) prediction model of CSC based on grid search optimized is proposed. Compared with the traditional machine learning model, the model has better prediction accuracy and generalization ability...

Bioinformatics prediction of function of T-cell exhaustion related genes in ischemic stroke.

Ischemic stroke (IS) is a multifactorial disease caused by the interaction of a variety of environmental and genetic factors, which can lead to severe disability and heavy social burden. This study aimed to find potential biomarkers related to T cell exhaustion (TEX) in IS. Based on the GSE16561 dataset, differentially expressed genes (DEGs) were screened from IS and control groups, and their enri...

The Innovation Paradox in Emerging Pharmaceutical Markets: Barriers and Opportunities for Sustainable Development.

Emerging pharmaceutical markets like Brazil, India, and China have seen significant growth due to rising medication demand, expanding middle-class acc...

Guided multi-objective generative AI to enhance structure-based drug design.

Generative AI has the potential to revolutionize drug discovery. Yet, despite recent advances in deep learning, existing models cannot generate molecu...

Explainability of Protein Deep Learning Models.

Protein embeddings are the new main source of information about proteins, producing state-of-the-art solutions to many problems, including protein int...

Automating the Analysis of Substrate Reactivity through Environment Interaction Mapping.

Exploring the interaction configurations between substrates and atomic or molecular systems is crucial for various scientific and technological applic...

Drug-drug interaction prediction of traditional Chinese medicine based on graph attention networks.

Predicting drug-drug interactions (DDI) is crucial for preventing adverse reactions in patients and plays a vital role in drug design and development....

How generative Artificial Intelligence can transform drug discovery?

Generative Artificial Intelligence (Generative AI) is transforming drug discovery by enabling advanced analysis of complex biological and chemical dat...

Is Interaction Between Human and Artificial Intelligence-Driven Agents (Para)Social? A Scoping Review.

Despite the growing presence of artificial intelligence (AI)-based agents in human daily life, there remains a dearth of exploration and synthesized e...

AI in Neurology: Everything, Everywhere, all at Once PART 2: Speech, Sentience, Scruples, and Service.

Artificial intelligence (AI) applications are finding use in real-world neurological settings. Whereas part 1 of this 3-part review series focused on ...

Pharmacovigilance in the digital age: gaining insight from social media data.

Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous...

MultiV_Nm: a prediction method for 2'-O-methylation sites based on multi-view features.

As a crucial class of chemical modifications, 2'-O-methylation modification (abbreviated as Nm) is widely distributed in various organisms and plays a...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage...

An Integrated AI-PBPK Platform for Predicting Drug In Vivo Fate and Tissue Distribution in Human and Inter-Species Extrapolation.

Optimal pharmacokinetic (PK) profile, including tissue distribution, is pivotal for a drug achieving success in clinical trials. Traditionally, PK est...

Surfactant representation using COSMO screened charge density for adsorption isotherm prediction using Physics-Informed Neural Network (PINN).

Predicting surfactant adsorption using the currently available isotherm model is limited to one or two independent variables: equilibrium concentratio...

Leveraging Hospital Information Data for Effective Antibiotic Stewardship.

Clinical informatics has emerged as a valuable approach to enhance antimicrobial stewardship programs in healthcare settings. By integrating informati...

The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy.

Motor activity alterations are key symptoms of psychiatric disorders like schizophrenia. Actigraphy, a non-invasive monitoring method, shows promise i...

Enhancing image-based virtual try-on with Multi-Controlled Diffusion Models.

Image-based virtual try-on technology digitally overlays clothing onto images of individuals, enabling users to preview how garments fit without physi...

Role of artificial intelligence in cancer drug discovery and development.

The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform...

Unveiling the role of IL7R in metabolism-associated fatty liver disease leading to hepatocellular carcinoma through transcriptomic and machine learning approaches.

Dysregulation of hepatic metabolism is a crucial factor in the development of fatty liver disease and significantly increases the risk of hepatocellul...