BACKGROUND: Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer (GC). To facilitate this research, a cost- and time-effective method to analyze the mutation...
Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Nov 25, 2021
The accumulation of protein sequence and structure data allows researchers to obtain large amount of descriptive information, simultaneously it poses an urgent need for researchers to extract information from existing data efficiently and apply it to...
Studies in health technology and informatics
Nov 18, 2021
Using guideline-based clinical decision support systems (CDSSs) has improved clinical practice, especially during multidisciplinary tumour boards (MTBs) in cancer patient management. However, MTBs have been reported to be overcrowded, with limited ti...
Studies in health technology and informatics
Nov 18, 2021
There is a growing trend in building deep learning patient representations from health records to obtain a comprehensive view of a patient's data for machine learning tasks. This paper proposes a reproducible approach to generate patient pathways fro...
MOTIVATION: Traditional regression models are limited in outcome prediction due to their parametric nature. Current deep learning methods allow for various effects and interactions and have shown improved performance, but they typically need to be tr...
MOTIVATION: Digital pathology supports analysis of histopathological images using deep learning methods at a large-scale. However, applications of deep learning in this area have been limited by the complexities of configuration of the computational ...
Sarcopenia, characterized by a decline of skeletal muscle mass, has emerged as an important prognostic factor for cancer patients. Trunk computed tomography (CT) is a commonly used modality for assessment of cancer disease extent and treatment outcom...
Deep residual learning has shown great success in protein contact prediction. In this study, a new deep residual learning-based protein contact prediction model was developed. Comparing with previous models, a new type of residual block hybridizing 1...
With the rapid development of proteomics and the rapid increase of target molecules for drug action, computer-aided drug design (CADD) has become a basic task in drug discovery. One of the key challenges in CADD is molecular representation. High-qual...
Computational methods have become indispensable tools to accelerate the drug discovery process and alleviate the excessive dependence on time-consuming and labor-intensive experiments. Traditional feature-engineering approaches heavily rely on expert...
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