AI Medical Compendium Topic:
Databases, Factual

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Presentation Attack Detection on Limited-Resource Devices Using Deep Neural Classifiers Trained on Consistent Spectrogram Fragments.

Sensors (Basel, Switzerland)
The presented paper is concerned with detection of presentation attacks against unsupervised remote biometric speaker verification, using a well-known challenge-response scheme. We propose a novel approach to convolutional phoneme classifier training...

A weighted patient network-based framework for predicting chronic diseases using graph neural networks.

Scientific reports
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...

Aedes-AI: Neural network models of mosquito abundance.

PLoS computational biology
We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluat...

Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...

Fine-Tuning Word Embeddings for Hierarchical Representation of Data Using a Corpus and a Knowledge Base for Various Machine Learning Applications.

Computational and mathematical methods in medicine
Word embedding models have recently shown some capability to encode hierarchical information that exists in textual data. However, such models do not explicitly encode the hierarchical structure that exists among words. In this work, we propose a met...

Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

Gynecologic oncology
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...

Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.

Computational and mathematical methods in medicine
A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential popular microblog where people voice their opinions about daily issues. Recently, analyzing these o...

Deep-Learning-Based Stress Recognition with Spatial-Temporal Facial Information.

Sensors (Basel, Switzerland)
In recent times, as interest in stress control has increased, many studies on stress recognition have been conducted. Several studies have been based on physiological signals, but the disadvantage of this strategy is that it requires physiological-si...

Call for a Public Open Database of All Chemical Reactions.

Journal of chemical information and modeling
Today there exists no public, freely downloadable, comprehensive database of all known chemical reactions and associated information. Such a database not only would serve chemical sciences and technologies around the world but also would enable the p...

RDFNet: A Fast Caries Detection Method Incorporating Transformer Mechanism.

Computational and mathematical methods in medicine
Dental caries is a prevalent disease of the human oral cavity. Given the lack of research on digital images for caries detection, we construct a caries detection dataset based on the caries images annotated by professional dentists and propose RDFNet...