AIMC Topic: Humans

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An Analytical Review of Computational Drug Repurposing.

IEEE/ACM transactions on computational biology and bioinformatics
Drug repurposing is a vital function in pharmaceutical fields and has gained popularity in recent years in both the pharmaceutical industry and research community. It refers to the process of discovering new uses and indications for existing or faile...

A Fast Linear Neighborhood Similarity-Based Network Link Inference Method to Predict MicroRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
Increasing evidences revealed that microRNAs (miRNAs) play critical roles in important biological processes. The identification of disease-related miRNAs is critical to understand the molecular mechanisms of human diseases. Most existing computationa...

A Novel Drug Repositioning Approach Based on Collaborative Metric Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Computational drug repositioning, which is an efficient approach to find potential indications for drugs, has been used to increase the efficiency of drug development. The drug repositioning problem essentially is a top-K recommendation task that rec...

An Improved Muti-Task Learning Algorithm for Analyzing Cancer Survival Data.

IEEE/ACM transactions on computational biology and bioinformatics
Survival analysis is a popular branch of statistics. At present, many algorithms (like traditional multi-tasking learning model) cannot be applied well in practice because of censored data. Although using some model (like parametric regression model)...

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines.

IEEE/ACM transactions on computational biology and bioinformatics
High-throughput screening technologies have provided a large amount of drug sensitivity data for a panel of cancer cell lines and hundreds of compounds. Computational approaches to analyzing these data can benefit anticancer therapeutics by identifyi...

A Hybrid Supervised Approach to Human Population Identification Using Genomics Data.

IEEE/ACM transactions on computational biology and bioinformatics
Single nucleotide polymorphisms (SNPs) are one type of genetic variations and each SNP represents a difference in a single DNA building block, namely a nucleotide. Previous research demonstrated that SNPs can be used to identify the correct source po...

A Cascade of 2.5D CNN and Bidirectional CLSTM Network for Mitotic Cell Detection in 4D Microscopy Image.

IEEE/ACM transactions on computational biology and bioinformatics
Mitosis detection is one of the challenging steps in biomedical imaging research, which can be used to observe the cell behavior. Most of the already existing methods that are applied in detecting mitosis usually contain many nonmitotic events (norma...

Understanding risk factors for postoperative mortality in neonates based on explainable machine learning technology.

Journal of pediatric surgery
PURPOSE: We aimed to introduce an explainable machine learning technology to help clinicians understand the risk factors for neonatal postoperative mortality at different levels.

Tracking stress via the computer mouse? Promises and challenges of a potential behavioral stress marker.

Behavior research methods
Computer mouse tracking offers a simple and cost-efficient way to gather continuous behavioral data and has mostly been utilized in psychological science to study cognitive processes. The present study extends the potential applicability of computer ...

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings.

Neural networks : the official journal of the International Neural Network Society
Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a ...