AI Medical Compendium Topic

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Hepatitis C viral load and genotypes among Nigerian subjects with chronic infection and implication for patient management: a retrospective review of data.

The Pan African medical journal
INTRODUCTION: Hepatitis C Virus (HCV) is highly infectious with no currently available vaccine. Prior to treatment, it is recommended to confirm HCV infection with either quantitative or qualitative nucleic acid test. Access to these assays in Nigeri...

Acute hyperglycaemia in cystic fibrosis pulmonary exacerbations.

Endocrinology, diabetes & metabolism
BACKGROUND: Hyperglycaemia may contribute to failure to recover from pulmonary exacerbations in cystic fibrosis (CF). We aimed to evaluate the prevalence and mechanism of hyperglycaemia during and post-exacerbations.

Design and rationale of an intelligent algorithm to detect BuRnoUt in HeaLthcare workers in COVID era using ECG and artificiaL intelligence: The BRUCEE-LI study.

Indian heart journal
BACKGROUND: There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associated with electrocardiographic changes detectable by artificial intelligence (AI).

Evaluation of incomplete maternal smoking data using machine learning algorithms: a study from the Medical Birth Registry of Norway.

BMC pregnancy and childbirth
BACKGROUND: The Medical Birth Registry of Norway (MBRN) provides national coverage of all births. While retrieval of most of the information in the birth records is mandatory, mothers may refrain to provide information on her smoking status. The prop...

Identification of prognostic factors for pediatric myocarditis with a random forests algorithm-assisted approach.

Pediatric research
BACKGROUND: Pediatric myocarditis is a rare disease with substantial mortality. Little is known regarding its prognostic factors. We hypothesize that certain comorbidities and procedural needs may increase risks of poor outcomes. This study aims to i...

Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.

Journal of the American Heart Association
Background Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community-based interventions have been shown to be both effective and cost-effective in preventing cardiovascul...

Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone.

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

Nutrients
The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the current and near-future health systems, given the association of these conditions with different co...

Untangling the complexity of multimorbidity with machine learning.

Mechanisms of ageing and development
The prevalence of multimorbidity has been increasing in recent years, posing a major burden for health care delivery and service. Understanding its determinants and impact is proving to be a challenge yet it offers new opportunities for research to g...

Improving disaggregation models of malaria incidence by ensembling non-linear models of prevalence.

Spatial and spatio-temporal epidemiology
Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable routine surveillance data of malaria incidence, typically aggregated to administrative units, is becoming more widely available. Disaggregation regress...