AIMC Topic:
Databases, Factual
Clear Filters Showing 2051 to 2060 of 2956 articles
Automatically measuring brain ventricular volume within PACS using artificial intelligence.
PloS one
Mar 15, 2018
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and...
Development of an information retrieval tool for biomedical patents.
Computer methods and programs in biomedicine
Mar 14, 2018
BACKGROUND AND OBJECTIVE: The volume of biomedical literature has been increasing in the last years. Patent documents have also followed this trend, being important sources of biomedical knowledge, technical details and curated data, which are put to...
Impact of database quality in knowledge-based treatment planning for prostate cancer.
Practical radiation oncology
Mar 13, 2018
PURPOSE: This article investigates dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared with using a conventional, clinical plan database.
The design and validation of a hybrid digital-signal-processing plug-in for traditional cochlear implant speech processors.
Computer methods and programs in biomedicine
Mar 12, 2018
BACKGROUND AND OBJECTIVE: Cochlear implants (CIs) are electronic devices restoring partial hearing to deaf individuals with profound hearing loss. In this paper, a new plug-in for traditional IIR filter-banks (FBs) is presented for cochlear implants ...
Biomedical image classification based on a cascade of an SVM with a reject option and subspace analysis.
Computers in biology and medicine
Mar 12, 2018
Automated biomedical image classification could confront the challenges of high level noise, image blur, illumination variation and complicated geometric correspondence among various categorical biomedical patterns in practice. To handle these challe...
Training replicable predictors in multiple studies.
Proceedings of the National Academy of Sciences of the United States of America
Mar 12, 2018
This article considers replicability of the performance of predictors across studies. We suggest a general approach to investigating this issue, based on ensembles of prediction models trained on different studies. We quantify how the common practice...
Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.
Health services research
Mar 11, 2018
OBJECTIVE: To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending.
Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.
BioMed research international
Mar 7, 2018
Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians...
A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.
Journal of healthcare engineering
Mar 7, 2018
The prevention, evaluation, and treatment of hypertension have attracted increasing attention in recent years. As photoplethysmography (PPG) technology has been widely applied to wearable sensors, the noninvasive estimation of blood pressure (BP) usi...
Humans
Neural Networks, Computer
Female
Critical Care
Databases, Factual
Blood Pressure Determination
Middle Aged
Young Adult
Reproducibility of Results
Blood Pressure
Aged
Hypertension
Pattern Recognition, Automated
Pulse Wave Analysis
Aged, 80 and over
Adult
Photoplethysmography
Systole
Electrocardiography
Male
Diastole
Comorbidity Scoring with Causal Disease Networks.
IEEE/ACM transactions on computational biology and bioinformatics
Mar 6, 2018
In recent years, there has been numerous studies constructing a disease network with diverse sources of data. Many researchers attempted to extend the usage of the disease network by employing machine learning algorithms on various problems such as p...
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