AIMC Topic: Humans

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Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

Journal of bioinformatics and computational biology
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...

Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

BMC bioinformatics
BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine L...

Data integration by fuzzy similarity-based hierarchical clustering.

BMC bioinformatics
BACKGROUND: High throughput methods, in biological and biomedical fields, acquire a large number of molecular parameters or omics data by a single experiment. Combining these omics data can significantly increase the capability for recovering fine-tu...

Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer.

Scientific reports
Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC...

A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes.

Nature communications
Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in the development of optimized small-molecule compounds. Current approaches cannot identif...

Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning.

Cells
High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes ...

End-to-End Training for Compound Expression Recognition.

Sensors (Basel, Switzerland)
For a long time, expressions have been something that human beings are proud of. That is an essential difference between us and machines. With the development of computers, we are more eager to develop communication between humans and machines, espec...

Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?

Sensors (Basel, Switzerland)
Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sens...

Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques.

Journal of medical Internet research
BACKGROUND: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which...

Cancer Informatics in 2019: Deep Learning Takes Center Stage.

Yearbook of medical informatics
OBJECTIVE: To summarize significant research contributions on cancer informatics published in 2019.