AIMC Topic: Artificial Intelligence

Clear Filters Showing 7591 to 7600 of 26332 articles

Augmenting DMTA using predictive AI modelling at AstraZeneca.

Drug discovery today
Design-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are ide...

Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch Using Well-Tempered Metadynamics Simulations.

Journal of chemical information and modeling
The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that mediates biological signals to control various complicated cellular functions. It plays a crucial role in environmental sensing and xenobiotic metabolism. Dysregulati...

Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design.

Journal of chemical information and modeling
Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from t...

Algorithms for Liver Segmentation in Computed Tomography Scans: A Historical Perspective.

Sensors (Basel, Switzerland)
Oncology has emerged as a crucial field of study in the domain of medicine. Computed tomography has gained widespread adoption as a radiological modality for the identification and characterisation of pathologies, particularly in oncology, enabling p...

Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network.

BMC medical imaging
OBJECTIVE: This study aims to classify tongue lesion types using tongue images utilizing Deep Convolutional Neural Networks (DCNNs).

Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.

Scientific reports
The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the un...

Generative AI in Medical Practice: In-Depth Exploration of Privacy and Security Challenges.

Journal of medical Internet research
As advances in artificial intelligence (AI) continue to transform and revolutionize the field of medicine, understanding the potential uses of generative AI in health care becomes increasingly important. Generative AI, including models such as genera...

3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients  with Multiple Myeloma using Whole-body MRI.

Journal of medical systems
Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted ...

Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis.

Journal of biomedical informatics
OBJECTIVE: Large language models (LLMs) such as ChatGPT are increasingly explored in medical domains. However, the absence of standard guidelines for performance evaluation has led to methodological inconsistencies. This study aims to summarize the a...

Artificial intelligence in paediatrics: Current events and challenges.

Anales de pediatria
This article examines the use of artificial intelligence (AI) in the field of paediatric care within the framework of the 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral and Polyprofessional). It highlights...