AI Medical Compendium Topic:
Models, Statistical

Clear Filters Showing 661 to 670 of 1240 articles

Laplacian mixture modeling for network analysis and unsupervised learning on graphs.

PloS one
Laplacian mixture models identify overlapping regions of influence in unlabeled graph and network data in a scalable and computationally efficient way, yielding useful low-dimensional representations. By combining Laplacian eigenspace and finite mixt...

Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...

Predicting residential structures from open source remotely enumerated data using machine learning.

PloS one
Having accurate maps depicting the locations of residential buildings across a region benefits a range of sectors. This is particularly true for public health programs focused on delivering services at the household level, such as indoor residual spr...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

Medicina intensiva
INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. Howev...

A New Approach for Advertising CTR Prediction Based on Deep Neural Network via Attention Mechanism.

Computational and mathematical methods in medicine
Click-through rate prediction is critical in Internet advertising and affects web publisher's profits and advertiser's payment. The traditional method of obtaining features using feature extraction did not consider the sparseness of advertising data ...

A dynamic model for predicting graft function in kidney recipients' upcoming follow up visits: A clinical application of artificial neural network.

International journal of medical informatics
BACKGROUND: Predicting the function of transplanted kidneys would help clinicians in individualized medical interventions. We aimed to develop and validate a predictive tool for a future value of estimated glomerular filtration rate (eGFR) at upcomin...

A comparison of word embeddings for the biomedical natural language processing.

Journal of biomedical informatics
BACKGROUND: Word embeddings have been prevalently used in biomedical Natural Language Processing (NLP) applications due to the ability of the vector representations being able to capture useful semantic properties and linguistic relationships between...

Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Surgical oncology
Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting ...

Identifying health information technology related safety event reports from patient safety event report databases.

Journal of biomedical informatics
OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model featu...

Universal method for robust detection of circadian state from gene expression.

Proceedings of the National Academy of Sciences of the United States of America
Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly imp...