[HTML][HTML] Integration strategies of multi-omics data for machine learning analysis
Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …
number of omics data that seek to portray many different but complementary biological …
A roadmap for multi-omics data integration using deep learning
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …
amount of multi-omics data for various applications. These data have revolutionized …
Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine
S Vadapalli, H Abdelhalim, S Zeeshan… - Briefings in …, 2022 - academic.oup.com
Precision medicine uses genetic, environmental and lifestyle factors to more accurately
diagnose and treat disease in specific groups of patients, and it is considered one of the …
diagnose and treat disease in specific groups of patients, and it is considered one of the …
[HTML][HTML] Towards a universal privacy model for electronic health record systems: an ontology and machine learning approach
This paper proposed a novel privacy model for Electronic Health Records (EHR) systems
utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It …
utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It …
[HTML][HTML] Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review
L Schneider, S Laiouar-Pedari, S Kuntz… - European journal of …, 2022 - Elsevier
Background Over the past decade, the development of molecular high-throughput methods
(omics) increased rapidly and provided new insights for cancer research. In parallel, deep …
(omics) increased rapidly and provided new insights for cancer research. In parallel, deep …
[HTML][HTML] Artificial intelligence, healthcare, clinical genomics, and pharmacogenomics approaches in precision medicine
Precision medicine has greatly aided in improving health outcomes using earlier diagnosis
and better prognosis for chronic diseases. It makes use of clinical data associated with the …
and better prognosis for chronic diseases. It makes use of clinical data associated with the …
[HTML][HTML] Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning …
Cardiovascular disease (CVD) is the leading cause of mortality and loss of disability
adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) …
adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) …
[HTML][HTML] Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases
Abstract Intellectual and Developmental Disabilities (IDDs), such as Down syndrome,
Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth …
Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth …
[HTML][HTML] Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility
KK Patel, C Venkatesan, H Abdelhalim, S Zeeshan… - Human genomics, 2023 - Springer
Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular
disease (CVD) deaths in the USA and around the globe. Due to the complex nature …
disease (CVD) deaths in the USA and around the globe. Due to the complex nature …
[HTML][HTML] Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation
In healthcare, machine learning (ML) shows significant potential to augment patient care,
improve population health, and streamline healthcare workflows. Realizing its full potential …
improve population health, and streamline healthcare workflows. Realizing its full potential …