AIMC Topic: Prognosis

Clear Filters Showing 2931 to 2940 of 3837 articles

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows.

BMC medical informatics and decision making
BACKGROUND: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patient...

Predictors of short-term and long-term incontinence after robot-assisted radical prostatectomy.

The Journal of international medical research
Purpose To determine retrospectively the prognostic factors for urinary incontinence following robot-assisted radical prostatectomy (RARP). Methods Altogether, 180 patients with localized prostate cancer underwent RARP (same surgeon). Preoperative ph...

Fuzzy Evidential Network and Its Application as Medical Prognosis and Diagnosis Models.

Journal of biomedical informatics
Uncertainty is one of the important facts of the medical knowledge. Medical prognosis and diagnosis, as the essential parts of medical knowledge, is affected by different aspects of uncertainty, which must be managed. In the previous studies, differe...

Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data.

BMC medical informatics and decision making
BACKGROUND: Machine learning algorithms hold potential for improved prediction of all-cause mortality in cardiovascular patients, yet have not previously been developed with high-quality population data. This study compared four popular machine learn...

Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

PloS one
BACKGROUND: Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patien...

A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation.

Journal of biomedical informatics
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes involved in breast cancer can be identified by immunohistochemistry. However, this method has problems arising from the intra-o...

Automatic prediction of coronary artery disease from clinical narratives.

Journal of biomedical informatics
Coronary Artery Disease (CAD) is not only the most common form of heart disease, but also the leading cause of death in both men and women (Coronary Artery Disease: MedlinePlus, 2015). We present a system that is able to automatically predict whether...

Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy.

PloS one
PURPOSE: Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that using a limited area. We investigated if d...