AIMC Topic: Noncommunicable Diseases

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Machine Learning Approach to Study Social Determinants of Chronic Illness in India: A Comparative Analysis.

Indian journal of public health
BACKGROUND: Several studies on noncommunicable diseases (NCDs) have been carried out worldwide, the basis of most of which is the identification of risk factors-modifiable (or behavioral) and metabolic. Majority of the NCDs are due to sociodemographi...

Can ChatGPT provide appropriate meal plans for NCD patients?

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVES: Dietary habits significantly affect health conditions and are closely related to the onset and progression of non-communicable diseases (NCDs). Consequently, a well-balanced diet plays an important role in lessening the effects of various...

XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction.

International journal of environmental research and public health
Smoking-induced noncommunicable diseases (SiNCDs) have become a significant threat to public health and cause of death globally. In the last decade, numerous studies have been proposed using artificial intelligence techniques to predict the risk of d...

Patterns and correlates of physical activity in adult Norwegians: a forecasted evolution up to 2025 based on machine learning approach.

BMC public health
BACKGROUND: As other westerns countries, a large portion of Norwegians do not meet the minimum recommendations for weekly physical activity (PA). One of the primary targets of the WHO's Global action plan for the prevention and control of noncommunic...

A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is one of the main causes of toxicity and treatment inefficacy. This work focuses on non-communicable diseases (NCDs), the non-transmissible and long-lasting diseases since they are the leading ca...

Learning Doctors' Medicine Prescription Pattern for Chronic Disease Treatment by Mining Electronic Health Records: A Multi-Task Learning Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Increasing learning ability from massive medical data and building learning methods robust to data quality issues are key factors toward building data-driven clinical decision support systems for medicine prescription decision support. Here, we attem...

The sky's the limit: improving satellite imagery data literacy to address non-communicable diseases.

International health
Low-and middle-income countries experience 77% of the world's premature deaths caused by non-communicable diseases, and their underlying health determinant data are often scarce and inaccurate. Improving satellite imagery data literacy worldwide is a...

A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

European journal of public health
Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (MASLD), atherogenic dyslipidaemia (ATD), and chronic kidney disease (CKD). The absence of reliable t...

Role of artificial intelligence in early identification and risk evaluation of non-communicable diseases: a bibliometric analysis of global research trends.

BMJ open
OBJECTIVE: This study aims to shed light on the transformative potential of artificial intelligence (AI) in the early detection and risk assessment of non-communicable diseases (NCDs).