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Chronic Disease

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Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

Computational intelligence and neuroscience
It was to explore the application value of health cloud service platform based on data mining algorithm and wireless network in the analysis of psychosocial factors and psychological characteristics of personality of patients with chronic diseases. B...

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.

The Journal of asthma : official journal of the Association for the Care of Asthma
OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. This study aimed to investigate different machine learning models and suggested the most effective on...

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction.

Frontiers in public health
Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has therefore become an important research area to enhance patient survival rates. Several research studies have reported classification approaches for specific di...

A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions.

Sensors (Basel, Switzerland)
This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on Pu...

Network analytics and machine learning for predicting length of stay in elderly patients with chronic diseases at point of admission.

BMC medical informatics and decision making
BACKGROUND: An aging population with a burden of chronic diseases puts increasing pressure on health care systems. Early prediction of the hospital length of stay (LOS) can be useful in optimizing the allocation of medical resources, and improving he...

Identification and Prediction of Chronic Diseases Using Machine Learning Approach.

Journal of healthcare engineering
Nowadays, humans face various diseases due to the current environmental condition and their living habits. The identification and prediction of such diseases at their earlier stages are much important, so as to prevent the extremity of it. It is diff...

Machine learning for predicting chronic diseases: a systematic review.

Public health
OBJECTIVES: We aimed to review the literature regarding the use of machine learning to predict chronic diseases.

Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

Scientific reports
For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routine blood markers has proven to be clinically appropriate in primary care. We present a novel approach...

Computational models in inflammatory bowel disease.

Clinical and translational science
Inflammatory bowel disease (IBD) is a chronic and relapsing disease with multiple underlying influences and notable heterogeneity among its clinical and response-to-treatment phenotypes. There is no cure for IBD, and none of the currently available t...

Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images.

Scientific reports
Central serous chorioretinopathy (CSC) is one of the most common macular diseases that can reduce the quality of life of patients. This study aimed to build a deep learning-based classification model using multiple spectral domain optical coherence t...