AIMC Topic: Communicable Diseases

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Deep Learning for Automated Liver Segmentation to Aid in the Study of Infectious Diseases in Nonhuman Primates.

Academic radiology
With the advent of deep learning, convolutional neural networks (CNNs) have evolved as an effective method for the automated segmentation of different tissues in medical image analysis. In certain infectious diseases, the liver is one of the more hig...

Digitalization, clinical microbiology and infectious diseases.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

Image analysis and artificial intelligence in infectious disease diagnostics.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Microbiologists are valued for their time-honed skills in image analysis, including identification of pathogens and inflammatory context in Gram stains, ova and parasite preparations, blood smears and histopathologic slides. They also mus...

Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.

Scientific reports
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...

Multi-Modal Diagnosis of Infectious Diseases in the Developing World.

IEEE journal of biomedical and health informatics
In low and middle income countries, infectious diseases continue to have a significant impact, particularly amongst the poorest in society. Tetanus and hand foot and mouth disease (HFMD) are two such diseases and, in both, death is associated with au...

Identification of infectious disease-associated host genes using machine learning techniques.

BMC bioinformatics
BACKGROUND: With the global spread of multidrug resistance in pathogenic microbes, infectious diseases emerge as a key public health concern of the recent time. Identification of host genes associated with infectious diseases will improve our underst...

A novel model for malaria prediction based on ensemble algorithms.

PloS one
BACKGROUND AND OBJECTIVE: Most previous studies adopted single traditional time series models to predict incidences of malaria. A single model cannot effectively capture all the properties of the data structure. However, a stacking architecture can s...

Location of sources in reaction-diffusion equations using support vector machines.

PloS one
The reaction-diffusion equation serves to model systems in the diffusion regime with sources. Specific applications include diffusion processes in chemical reactions, as well as the propagation of species, diseases, and populations in general. In som...

Ontology based mining of pathogen-disease associations from literature.

Journal of biomedical semantics
BACKGROUND: Infectious diseases claim millions of lives especially in the developing countries each year. Identification of causative pathogens accurately and rapidly plays a key role in the success of treatment. To support infectious disease researc...

Machine learning for clinical decision support in infectious diseases: a narrative review of current applications.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID).