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 …
Interpretable machine learning methods for predictions in systems biology from omics data
Machine learning has become a powerful tool for systems biologists, from diagnosing
cancer to optimizing kinetic models and predicting the state, growth dynamics, or type of a …
cancer to optimizing kinetic models and predicting the state, growth dynamics, or type of a …
Deep learning-based weather prediction: a survey
Weather forecasting plays a fundamental role in the early warning of weather impacts on
various aspects of human livelihood. For instance, weather forecasting provides decision …
various aspects of human livelihood. For instance, weather forecasting provides decision …
Current challenges for unseen-epitope TCR interaction prediction and a new perspective derived from image classification
The prediction of epitope recognition by T-cell receptors (TCRs) has seen many
advancements in recent years, with several methods now available that can predict …
advancements in recent years, with several methods now available that can predict …
Deep‐learning artificial intelligence analysis of clinical variables predicts mortality in COVID‐19 patients
JS Zhu, P Ge, C Jiang, Y Zhang, X Li… - Journal of the …, 2020 - Wiley Online Library
Objective The large number of clinical variables associated with coronavirus disease 2019
(COVID‐19) infection makes it challenging for frontline physicians to effectively triage COVID …
(COVID‐19) infection makes it challenging for frontline physicians to effectively triage COVID …
Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables
Background This study aimed to develop a deep-learning model and a risk-score system
using clinical variables to predict intensive care unit (ICU) admission and in-hospital …
using clinical variables to predict intensive care unit (ICU) admission and in-hospital …
Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction
Accurate credit risk prediction can help companies avoid bankruptcies and make
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction
Abstract Human Leukocyte Antigen (HLA) is a type of molecule residing on the surfaces of
most human cells and exerts an essential role in the immune system responding to the …
most human cells and exerts an essential role in the immune system responding to the …
Classifying breast cancer subtypes using deep neural networks based on multi-omics data
With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference
between various subtypes, so as to infer the underlying mechanisms. Given the available …
between various subtypes, so as to infer the underlying mechanisms. Given the available …
SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers
Survival models exist to study relationships between biomarkers and treatment effects. Deep
learning-powered survival models supersede the classical Cox proportional hazards …
learning-powered survival models supersede the classical Cox proportional hazards …