Latest AI and machine learning research in primary care for healthcare professionals.
Over the last four decades, there has been a pursuit for a non-invasive solution for glucose measurement, but there is not yet any viable product released. Of the many sensor modalities tried, the combination of electrical and optical measurement is among the most promising for continuous measurements. Although non-invasive prediction of exact glucose levels may seem futile, prediction of their tr...
The aim of the present study was a comparative investigation of water and 70% ethanol extracts derived from yellow and red onion ( L.) peels against diabetes and diabetic complications. The total phenolic contents (TPCs) and total flavonoid contents (TFCs) of each cultivar, measured to assess phytochemical characteristics, showed a direct correlation with the in vitro antioxidant effects. Among th...
Drug research and development is a long-term and complicated process with the involvement of multidisciplinary, multi-sector cooperation and regulatio...
BACKGROUND: American Indians (AIs) have significantly higher rates of diet-related chronic diseases than other racial/ethnic groups, and many live in ...
Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of...
An adrenal incidentaloma (AI) is an adrenal mass incidentally found via a radiological modality, independent of an endocrinological investigation. In ...
Software testing of knowledge-based clinical decision support systems is challenging, labor intensive, and expensive; yet, testing is necessary since ...
U.S. military veterans who were discharged from service for misconduct are at high risk for homelessness. Stratifying homelessness risk based on both ...
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis)...
A computational phenotype is a set of clinically relevant and interesting characteristics that describe patients with a given condition. Various machi...
Over 75 million Americans have multiple concurrent chronic conditions and medical decision making for these patients is mostly based on retrospective ...
Toxicity is an important factor in failed drug development, and its efficient identification and prediction is a major challenge in drug discovery. We...
The volume of high throughput screening data has considerably increased since the beginning of the automated biochemical and cell-based assays era. Th...
BACKGROUND: Diabetes mellitus is a deadly disorder in human which induce chronic complications. The streptozotocin (STZ)-induced diabetes in rat is th...
The review aims at providing current state of evidence in the field of medicine with fuzzy logic for diagnosing diseases. Literature reveals that fuzz...
Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient infor...
AIMS: Non-Caucasian migrants require dedicated approaches in diabetes management due to specific genetic; socio-cultural; demographic and anthropologi...
The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in...
The rapid development of information technology and data processing capabilities has led to the creation of new tools known as artificial intelligence...
BACKGROUND: Urinary 20-hydroxyeicosatetraenoic acid (20-HETE) has been associated with hypertension in women with elevated urinary cadmium (Cd) excret...