Latest AI and machine learning research in metabolic syndrome for healthcare professionals.
Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the common approach is to treat each disease separately. As age-associated diseases have common underlying mechanisms there is potential to tackle many diseases with the same pharmacological intervention. These are known as geroprotectors and could overcome the problems related to polypharmacy seen with the...
The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients effectively. This study used the nationwide cohort of South Korea to develop a machine learning model to predict prognosis based on sociodemographic and medical information. Of 10,237 COVID-19 patients, 228 (2.2%) died, 7772 (75.9%) recovered, and 2237...
Short chain fatty acids (SCFA) are the main products of indigestible carbohydrates undergoing bacterial fermentation in the hindgut, which are related...
Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquatic and ecological environmental systems. These poll...
Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is ...
Due to the growing public awareness of cardiovascular disease (CVD), blood pressure (BP) estimation models have been developed based on physiological ...
Background Real-world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts-a cruc...
As is known, cerebral stroke has become one of the main diseases endangering people's health; ischaemic strokes accounts for approximately 85% of cere...
BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a...
BACKGROUND: To date, the missed diagnosis rate of pulmonary hypertension (PH) was high, and there has been limited development of a rapid, simple, and...
Current BP measurements are on the basis of traditional BP cuff approaches. Ambulatory BP monitoring, at 15- to 30-minute intervals usually over 24 ho...
We studied the use of a rotating multi-layer 3D Light Detection And Ranging (LiDAR) sensor (specifically the Velodyne HDL-32E) mounted on a social rob...
Background Women with congenital heart disease are considered at high risk for adverse events. Therefore, we aim to establish 2 prediction models for ...
The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming...
This study sought to evaluate the association of breast arterial calcification (BAC) on breast screening mammography with the Coronary Artery Disease-...
BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EP...
A 3-week-old boy with viral gastroenteritis was by error given 200 mL 1 mmol/mL hypertonic saline intravenously instead of isotonic saline. His plasma...
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabet...
Blood glycemic control is crucial for minimizing severe side effects in diabetes mellitus. Currently, two opposing treatment approaches exist: in form...
Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection. State-of-the-art continuous BP measurement metho...