AIMC Topic: Models, Statistical

Clear Filters Showing 811 to 820 of 1301 articles

A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs.

Science (New York, N.Y.)
Learning from a few examples and generalizing to markedly different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems neuroscience, we introduce...

Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.

Computational and mathematical methods in medicine
Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system...

Design and application of tumor prediction model based on statistical method.

Computer assisted surgery (Abingdon, England)
Two prediction models for tumor prediction based on logistic regression and BP neural network were proposed in this paper; a sensitivity analysis of risk factors was also conducted. The two protocols will be implemented in the R language and demonstr...

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate ...

Unified Deep Learning Architecture for Modeling Biology Sequence.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of the spatial structure or function of biological macromolecules based on their sequences remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, long-range interaction, co...

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

Environmental pollution (Barking, Essex : 1987)
Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model lon...

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models.

Journal of biomedical semantics
BACKGROUND: In this paper we present the approach that we employed to deal with large scale multi-label semantic indexing of biomedical papers. This work was mainly implemented within the context of the BioASQ challenge (2013-2017), a challenge conce...

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

BMC systems biology
BACKGROUND: High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets deri...

Validation of a Machine Learning Approach for Venous Thromboembolism Risk Prediction in Oncology.

Disease markers
Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictors, which could be useful to devise a web interface for VTE risk stratification in chemotherapy-treat...

Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems.

Sensors (Basel, Switzerland)
Cyber-physical systems (CPS) have received much attention from both academia and industry. An increasing number of functions in CPS are provided in the way of services, which gives rise to an urgent task, that is, how to recommend the suitable servic...