AIMC Topic: Software

Clear Filters Showing 2861 to 2870 of 3675 articles

deepFPlearn +: enhancing toxicity prediction across the chemical universe using graph neural networks.

Bioinformatics (Oxford, England)
SUMMARY: Sophisticated approaches for the in silico prediction of toxicity are required to support the risk assessment of chemicals. The number of chemicals on the global chemical market and the speed of chemical innovation stand in massive contrast ...

Are multi-detector computed tomography and cone-beam computed tomography exams and software accurate to measure the upper airway? A systematic review.

European journal of orthodontics
BACKGROUND: Cone-beam computed tomography (CBCT) has several applications in various fields of dental medicine such as diagnosis and treatment planning. When compared to computed tomography (CT), CBCT's radiation exposure dose is decreased by 3%-20%....

CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation.

Briefings in bioinformatics
Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this...

Leveraging the efficiency and transparency of artificial intelligence-driven visual Chatbot through smart prompt learning concept.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)

Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification.

Bioinformatics (Oxford, England)
SUMMARY: Federated learning enables collaboration in medicine, where data is scattered across multiple centers without the need to aggregate the data in a central cloud. While, in general, machine learning models can be applied to a wide range of dat...

Automated exploitation of deep learning for cancer patient stratification across multiple types.

Bioinformatics (Oxford, England)
MOTIVATION: Recent frameworks based on deep learning have been developed to identify cancer subtypes from high-throughput gene expression profiles. Unfortunately, the performance of deep learning is highly dependent on its neural network architecture...

THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.

Bioinformatics (Oxford, England)
MOTIVATION: Quantitative determination of protein thermodynamic stability is a critical step in protein and drug design. Reliable prediction of protein stability changes caused by point variations contributes to developing-related fields. Over the pa...

Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study.

Studies in health technology and informatics
Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practic...

Clinical Acronym Disambiguation via ChatGPT and BING.

Studies in health technology and informatics
Clinical texts are written with acronyms, abbreviations and medical jargon expressions to save time. This hinders full comprehension not just for medical experts but also laypeople. This paper attempts to disambiguate acronyms with their given contex...