Neural networks : the official journal of the International Neural Network Society
Mar 20, 2020
Humans are continuously exposed to a stream of visual data with a natural temporal structure. However, most successful computer vision algorithms work at image level, completely discarding the precious information carried by motion. In this paper, we...
Medical & biological engineering & computing
Mar 20, 2020
X-ray images play an important role in providing physicians with satisfactory information correlated to fractures and diseases; unfortunately, most of these images suffer from low contrast and poor quality. Thus, enhancement of the image will increas...
International journal of molecular sciences
Mar 19, 2020
Drug-induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized and candidate drugs, and predicting hepatotoxicity from the chemical structure of a substance remains a task worth pursuing. Such an approach is c...
Neural networks : the official journal of the International Neural Network Society
Mar 18, 2020
Emergency department (ED) overcrowding is a global condition that severely worsens attention to patients, increases clinical risks and affects hospital cost management. A correct and early prediction of ED's admission is of high value and a motivatio...
Machine learning is a powerful tool for creating computational models relating brain function to behavior, and its use is becoming widespread in neuroscience. However, these models are complex and often hard to interpret, making it difficult to evalu...
Drug-disease association is an important piece of information which participates in all stages of drug repositioning. Although the number of drug-disease associations identified by high-throughput technologies is increasing, the experimental methods ...
For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn spat...
BACKGROUND: Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morbidity and mortality, especially in the elderly. With a rapid growth of the elderly population in recent years, lung cancer prevention and control are ...
Similarity-based search of sequence collections is a core task in bioinformatics, one dominated for most of the genomic era by exact and heuristic alignment-based algorithms. However, even efficient heuristics such as BLAST may not scale to the data ...
BACKGROUND: Screening programs use mammography as primary diagnostic tool for detecting breast cancer at an early stage. The diagnosis of some lesions, such as microcalcifications, is still difficult today for radiologists. In this paper, we proposed...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.