AIMC Topic: DNA Methylation
Clear Filters Showing 71 to 80 of 254 articles
Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.
Epigenomics
Jul 29, 2024
This study investigates the altered expression and CpG methylation patterns of histone demethylase in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers. Leveraging TCGA-LIHC multi-omics data, we employe...
DeepPGD: A Deep Learning Model for DNA Methylation Prediction Using Temporal Convolution, BiLSTM, and Attention Mechanism.
International journal of molecular sciences
Jul 26, 2024
As part of the field of DNA methylation identification, this study tackles the challenge of enhancing recognition performance by introducing a specialized deep learning framework called DeepPGD. DNA methylation, a crucial biological modification, pla...
Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.
Translational psychiatry
Jul 15, 2024
The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression sig...
Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES).
Journal of Korean medical science
Jul 8, 2024
BACKGROUND: Sarcopenia, characterized by a progressive decline in muscle mass, strength, and function, is primarily attributable to aging. DNA methylation, influenced by both genetic predispositions and environmental exposures, plays a significant ro...
Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.
Journal of translational medicine
Jul 3, 2024
BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation at...
Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.
Neoplasia (New York, N.Y.)
Jun 28, 2024
Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the orig...
Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis.
Scientific reports
Jun 26, 2024
Detecting aberrant cell-free DNA (cfDNA) methylation is a promising strategy for lung cancer diagnosis. In this study, our aim is to identify methylation markers to distinguish patients with lung cancer from healthy individuals. Additionally, we soug...
Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic islets.
Scientific reports
Jun 25, 2024
Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple la...
A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.
Translational psychiatry
Jun 17, 2024
Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention ha...
Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia.
Computers in biology and medicine
Jun 13, 2024
BACKGROUND: Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and the fifth most common malignancy in children, necessitating advanced technologies for outcome prediction.
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32006
- Neural Networks, Computer 30221
- Algorithms 27397
- Deep Learning 26901
- Artificial Intelligence 24835
- Robotics 13387
- Image Processing, Computer-Assisted 9735
- Retrospective Studies 9342
- Magnetic Resonance Imaging 6346
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4865
- Support Vector Machine 4769
- Computational Biology 4332
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6775
- Sensors (Basel, Switzerland) 4794
- PloS one 4200
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1064
- Nature communications 1044
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 861
- Briefings in bioinformatics 853