AIMC Topic: Cross-Sectional Studies

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Application of machine learning techniques to the analysis and prediction of drug pharmacokinetics.

Journal of controlled release : official journal of the Controlled Release Society
In this review, we describe the current status and challenges in applying machine-learning techniques to the analysis and prediction of pharmacokinetic data. The theory of pharmacokinetics has been developed over decades on the basis of physiology an...

Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic prediction.

Abdominal radiology (New York)
PURPOSE: The purpose of this study is to compare fully automated CT-based measures of adipose tissue at the L1 level versus the standard L3 level for predicting mortality, which would allow for use at both chest (L1) and abdominal (L3) CT.

A parallel integrated learning technique of improved particle swarm optimization and BP neural network and its application.

Scientific reports
Swarm intelligence algorithm has attracted a lot of interest since its development, which has been proven to be effective in many application areas. In this study, an enhanced integrated learning technique of improved particle swarm optimization and ...

Artificial intelligence in medical education: a cross-sectional needs assessment.

BMC medical education
BACKGROUND: As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definitions need to be redefined for those who provide services in healthcare. This study examined the perce...

Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.

Scientific reports
To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. The subjects were divided into primipara and multipara, and the risk factors for the outcomes of indu...

A Deep Learning-Based Model for Predicting Abnormal Liver Function in Workers in the Automotive Manufacturing Industry: A Cross-Sectional Survey in Chongqing, China.

International journal of environmental research and public health
To identify the influencing factors and develop a predictive model for the risk of abnormal liver function in the automotive manufacturing industry works in Chongqing. Automotive manufacturing workers in Chongqing city surveyed during 2019-2021 were ...

A novel combination of corneal confocal microscopy, clinical features and artificial intelligence for evaluation of ocular surface pain.

PloS one
OBJECTIVES: To analyse various corneal nerve parameters using confocal microscopy along with systemic and orthoptic parameters in patients presenting with ocular surface pain using a random forest artificial intelligence (AI) model.

Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach.

Frontiers in public health
The world is witnessing an increasing number of senior adult residents who experience health issues. Healthcare innovation facilitates monitoring the health conditions of senior adults and reducing the burden on healthcare institutions. The study exp...

Survival analysis of localized prostate cancer with deep learning.

Scientific reports
In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthca...

Characteristics of Artificial Intelligence Clinical Trials in the Field of Healthcare: A Cross-Sectional Study on ClinicalTrials.gov.

International journal of environmental research and public health
Artificial intelligence (AI) has driven innovative transformation in healthcare service patterns, despite a lack of understanding of its performance in clinical practice. We conducted a cross-sectional analysis of AI-related trials in healthcare base...