AIMC Topic: Machine Learning

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Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms.

Journal of medical Internet research
BACKGROUND: An increasing number of doctor reviews are being generated by patients on the internet. These reviews address a diverse set of topics (features), including wait time, office staff, doctor's skills, and bedside manners. Most previous work ...

Development of 3D patient-based super-resolution digital breast phantoms using machine learning.

Physics in medicine and biology
Digital phantoms are important tools for optimization and evaluation of x-ray imaging systems, and should ideally reflect the 3D structure of human anatomy and its potential variability. In addition, they need to include a good level of detail at a h...

Annotation of enhanced radiographs for medical image retrieval with deep convolutional neural networks.

PloS one
The number of images taken per patient scan has rapidly increased due to advances in software, hardware and digital imaging in the medical domain. There is the need for medical image annotation systems that are accurate as manual annotation is imprac...

Applying machine learning to continuously monitored physiological data.

Journal of clinical monitoring and computing
The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for moni...

A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave.

BioMed research international
OBJECTIVE: In this study, machine learning was utilized to classify and predict pulse wave of hypertensive group and healthy group and assess the risk of hypertension by observing the dynamic change of the pulse wave and provide an objective referenc...

Machine learning improves prediction of delayed cerebral ischemia in patients with subarachnoid hemorrhage.

Journal of neurointerventional surgery
BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) is a severe complication in patients with aneurysmal subarachnoid hemorrhage. Several associated predictors have been previously identified. However, their predictive value is generally low. We ...

Prognostic models in primary biliary cholangitis.

Journal of autoimmunity
Risk prediction modelling is important to better understand the determinants of the course and outcome of PBC and to inform the risk across the disease continuum in PBC enabling risk-stratified follow-up care and personalised therapy. Current prognos...

Estimation of Neonatal Intestinal Perforation Associated with Necrotizing Enterocolitis by Machine Learning Reveals New Key Factors.

International journal of environmental research and public health
Intestinal perforation (IP) associated with necrotizing enterocolitis (NEC) is one of the leading causes of mortality in premature neonates; with major nutritional and neurodevelopmental sequelae. Since predicting which neonates will develop perforat...

A machine learning texture model for classifying lung cancer subtypes using preliminary bronchoscopic findings.

Medical physics
PURPOSE: Bronchoscopy is useful in lung cancer detection, but cannot be used to differentiate cancer types. A computer-aided diagnosis (CAD) system was proposed to distinguish malignant cancer types to achieve objective diagnoses.