AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Expanding the coverage of spatial proteomics: a machine learning approach.

Bioinformatics (Oxford, England)
MOTIVATION: Multiplexed protein imaging methods use a chosen set of markers and provide valuable information about complex tissue structure and cellular heterogeneity. However, the number of markers that can be measured in the same tissue sample is i...

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

Bioinformatics (Oxford, England)
MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next...

Deep centroid: a general deep cascade classifier for biomedical omics data classification.

Bioinformatics (Oxford, England)
MOTIVATION: Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent bia...

PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Effective drug delivery systems are paramount in enhancing pharmaceutical outcomes, particularly through the use of cell-penetrating peptides (CPPs). These peptides are gaining prominence due to their ability to penetrate eukaryotic cells...

Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes.

Bioinformatics (Oxford, England)
MOTIVATION: The human microbiome may impact the effectiveness of drugs by modulating their activities and toxicities. Predicting candidate microbes for drugs can facilitate the exploration of the therapeutic effects of drugs. Most recent methods conc...

Multi-indicator comparative evaluation for deep learning-based protein sequence design methods.

Bioinformatics (Oxford, England)
MOTIVATION: Proteins found in nature represent only a fraction of the vast space of possible proteins. Protein design presents an opportunity to explore and expand this protein landscape. Within protein design, protein sequence design plays a crucial...

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achi...

RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Bioinformatics (Oxford, England)
MOTIVATION: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the developmen...

Coracle-a machine learning framework to identify bacteria associated with continuous variables.

Bioinformatics (Oxford, England)
SUMMARY: We present Coracle, an artificial intelligence (AI) framework that can identify associations between bacterial communities and continuous variables. Coracle uses an ensemble approach of prominent feature selection methods and machine learnin...

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

Bioinformatics (Oxford, England)
MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diag...