AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Chronic Disease

Showing 181 to 190 of 290 articles

Clear Filters

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

Journal of medical Internet research
BACKGROUND: Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to dea...

Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.

International journal of chronic obstructive pulmonary disease
PURPOSE: The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD).

Recovery and compensation after robotic assisted gait training in chronic stroke survivors.

Disability and rehabilitation. Assistive technology
Gait re-education is a primary rehabilitation goal after stroke. In the last decades, robots with different mechanical structures have been extensively used in the clinical practice for gait training of stroke survivors. However, the effectiveness o...

Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Autism research : official journal of the International Society for Autism Research
Very little is known about the health problems experienced by individuals with autism spectrum disorder (ASD) throughout their life course. We retrospectively analyzed diagnostic codes associated with de-identified electronic health records using a m...

ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management.

Journal of biomedical informatics
New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, high...

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

Health services research
OBJECTIVE: To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending.

Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes.

Sensors (Basel, Switzerland)
Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent s...

Deep learning architectures for multi-label classification of intelligent health risk prediction.

BMC bioinformatics
BACKGROUND: Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could ...

Defining lower airway bacterial infection in children with chronic endobronchial disorders.

Pediatric pulmonology
BACKGROUND: Differentiating lower airway bacterial infection from possible upper airway contamination in children with endobronchial disorders undergoing bronchoalveolar lavage (BAL) is important for guiding management. A diagnostic bacterial load th...