AIMC Topic: Machine Learning

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Motion-compensated frame rate up-conversion in carotid ultrasound images using optical flow and manifold learning.

Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
OBJECTIVE: Carotid ultrasonography is a reliable and non-invasive method to evaluate atherosclerosis disease and its complications. B-mode cineloops are widely used to assess the severity of atherosclerosis and its progression; ho- wever, tracking ra...

Corneal thickness measurement by secondary speckle tracking and image processing using machine-learning algorithms.

Journal of biomedical optics
Corneal thickness (CoT) is an important tool in the evaluation process for several disorders and in the assessment of intraocular pressure. We present a method enabling high-precision measurement of CoT based on secondary speckle tracking and process...

The role of artificial intelligence and machine learning in predicting orthopaedic outcomes.

The bone & joint journal
This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datase...

A guide to machine learning for bacterial host attribution using genome sequence data.

Microbial genomics
With the ever-expanding number of available sequences from bacterial genomes, and the expectation that this data type will be the primary one generated from both diagnostic and research laboratories for the foreseeable future, then there is both an o...

Fuzzy cognitive map based approach for determining the risk of ischemic stroke.

IET systems biology
Stroke is the third major cause of mortality in the world. The diagnosis of stroke is a very complex issue considering controllable and uncontrollable factors. These factors include age, sex, blood pressure, diabetes, obesity, heart disease, smoking,...

Accuracy of Kalman Filtering in Forecasting Visual Field and Intraocular Pressure Trajectory in Patients With Ocular Hypertension.

JAMA ophthalmology
IMPORTANCE: Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely to progress to open-angle glaucoma can assist clinicians with deciding on the frequency of monitoring and the potential benefit of early treatment.

Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We s...