AI Medical Compendium Topic

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

Genomics

Showing 251 to 260 of 950 articles

Clear Filters

COMMUTE: Communication-efficient transfer learning for multi-site risk prediction.

Journal of biomedical informatics
OBJECTIVES: We propose a communication-efficient transfer learning approach (COMMUTE) that effectively incorporates multi-site healthcare data for training a risk prediction model in a target population of interest, accounting for challenges includin...

Machine learning applications for transcription level and phenotype predictions.

IUBMB life
Predicting phenotypes and complex traits from genomic variations has always been a big challenge in molecular biology, at least in part because the task is often complicated by the influences of external stimuli and the environment on regulation of g...

Fuzzy Logic as a Strategy for Combining Marker Statistics to Optimize Preselection of High-Density and Sequence Genotype Data.

Genes
The high dimensionality of genotype data available for genomic evaluations has presented a motivation for developing strategies to identify subsets of markers capable of increasing the accuracy of predictions compared to the current commercial single...

Systematic tissue annotations of genomics samples by modeling unstructured metadata.

Nature communications
There are currently >1.3 million human -omics samples that are publicly available. This valuable resource remains acutely underused because discovering particular samples from this ever-growing data collection remains a significant challenge. The maj...

LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome.

Mathematical biosciences and engineering : MBE
DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learni...

Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models.

PLoS computational biology
Multi-task deep learning (DL) models can accurately predict diverse genomic marks from sequence, but whether these models learn the causal relationships between genomic marks is unknown. Here, we describe Deep Mendelian Randomization (DeepMR), a meth...

EnsembleSplice: ensemble deep learning model for splice site prediction.

BMC bioinformatics
BACKGROUND: Identifying splice site regions is an important step in the genomic DNA sequencing pipelines of biomedical and pharmaceutical research. Within this research purview, efficient and accurate splice site detection is highly desirable, and a ...

DPProm: A Two-Layer Predictor for Identifying Promoters and Their Types on Phage Genome Using Deep Learning.

IEEE journal of biomedical and health informatics
With the number of phage genomes increasing, it is urgent to develop new bioinformatics methods for phage genome annotation. Promoter, a DNA region, is important for gene transcriptional regulation. In the era of post-genomics, the availability of da...

Obtaining genetics insights from deep learning via explainable artificial intelligence.

Nature reviews. Genetics
Artificial intelligence (AI) models based on deep learning now represent the state of the art for making functional predictions in genomics research. However, the underlying basis on which predictive models make such predictions is often unknown. For...

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning.

Genes
Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the prognostic power of computational histopathology and genomics, this paper constructs a multi-modality prognostic model for survival prediction. We collec...