AIMC Topic: Cholesterol

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Deep Learning-Based Kinetic Analysis in Paper-Based Analytical Cartridges Integrated with Field-Effect Transistors.

ACS nano
This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity cha...

Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression.

Scientific reports
The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this study to develop an authentic prediction model using a machine learning (ML) algorithm. The objecti...

The value of CT radiomics combined with deep transfer learning in predicting the nature of gallbladder polypoid lesions.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Computed tomography (CT) radiomics combined with deep transfer learning was used to identify cholesterol and adenomatous gallbladder polyps that have not been well evaluated before surgery.

Improved detection of cholesterol gallstones using quasi-material decomposition images generated from single-energy computed tomography images via deep learning.

Radiological physics and technology
In this study, we developed a method for generating quasi-material decomposition (quasi-MD) images from single-energy computed tomography (SECT) images using a deep convolutional neural network (DCNN). Our aim was to improve the detection of choleste...

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

Scientific reports
It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE)...

TRENDS IN CHOLESTEROL AND LIPOPROTEINS ARE ASSOCIATED WITH ACUTE RESPIRATORY DISTRESS SYNDROME INCIDENCE AND DEATH AMONG SEPSIS PATIENTS.

Shock (Augusta, Ga.)
Objective: Compare changes in cholesterol and lipoprotein levels occurring in septic patients with and without acute respiratory distress syndrome (ARDS) and by survivorship. Methods: We reanalyzed data from prospective sepsis studies. Cholesterol an...

Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.

Hypertension (Dallas, Tex. : 1979)
BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys i...

Evaluating the risk of hypertension in residents in primary care in Shanghai, China with machine learning algorithms.

Frontiers in public health
OBJECTIVE: The prevention of hypertension in primary care requires an effective and suitable hypertension risk assessment model. The aim of this study was to develop and compare the performances of three machine learning algorithms in predicting the ...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

Biochemical and biophysical research communications
The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this ...

Danshao Shugan Granule therapy for non-alcoholic fatty liver disease.

Lipids in health and disease
BACKGROUND: Danshao Shugan Granules (DSSG), a traditional Chinese medicine (TCM), is given to protect the liver. The objective is to evaluate the mechanisms of the effects of DSSG on non-alcoholic fatty liver disease (NAFLD).