AI Medical Compendium Topic

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Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research.

Scientific reports
Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional gr...

Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets.

Scientific reports
Identifying drug target genes in gene expression profiles is not straightforward. Because a drug targets proteins and not mRNAs, the mRNA expression of drug target genes is not always altered. In addition, the interaction between a drug and protein c...

Holographic deep learning for rapid optical screening of anthrax spores.

Science advances
Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be...

Detecting hospital-acquired infections: A document classification approach using support vector machines and gradient tree boosting.

Health informatics journal
Hospital-acquired infections pose a significant risk to patient health, while their surveillance is an additional workload for hospital staff. Our overall aim is to build a surveillance system that reliably detects all patient records that potentiall...

Generative Artificial Intelligence: Applications in Scientific Writing and Data Analysis in Wound Healing Research.

Advances in skin & wound care
Generative artificial intelligence (AI) models are a new technological development with vast research use cases among medical subspecialties. These powerful large language models offer a wide range of possibilities in wound care, from personalized pa...

An Integrated Fuzzy Neural Network and Topological Data Analysis for Molecular Graph Representation Learning and Property Forecasting.

Molecular informatics
Within a recent decade, graph neural network (GNN) has emerged as a powerful neural architecture for various graph-structured data modelling and task-driven representation learning problems. Recent studies have highlighted the remarkable capabilities...

Exploring the potential of large language model-based chatbots in challenges of ribosome profiling data analysis: a review.

Briefings in bioinformatics
Ribosome profiling (Ribo-seq) provides transcriptome-wide insights into protein synthesis dynamics, yet its analysis poses challenges, particularly for nonbioinformatics researchers. Large language model-based chatbots offer promising solutions by le...

Predicting Functional Surface Topographies Combining Topological Data Analysis and Deep Learning Across the Human Protein Universe.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Characterizing geometric and topological properties of protein structures encompassing surface pockets, interior cavities, and cross channels is important for understanding their functions. Our knowledge of protein structures has been greatly advance...

[Research progress of deep learning applications in mass spectrometry imaging data analysis].

Se pu = Chinese journal of chromatography
Mass spectrometry imaging (MSI) is a promising method for characterizing the spatial distribution of compounds. Given the diversified development of acquisition methods and continuous improvements in the sensitivity of this technology, both the total...