AIMC Topic: Cross-Sectional Studies

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VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer's disease prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a transitional state between normal aging and Alzheimer's disease (AD), and accurately predicting the progression trend of MCI is critical to the early prevention and treatment of AD. Brain...

Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study.

BMC medical education
BACKGROUND: Emerging artificial intelligence (AI) technologies have diverse applications in medicine. As AI tools advance towards clinical implementation, skills in how to use and interpret AI in a healthcare setting could become integral for physici...

Surgeon experience, robotic perioperative outcomes, and complications in gynecology.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: Robotic surgery is currently on the rise and has been widely applied all over the world. Gynecology offers great opportunities for the development of innovative techniques due to the magnitude of surgical needs. The aim of this study was t...

Status of robot-assisted artificial total joint arthroplasty in China: a cross-sectional survey of joint surgeons.

International orthopaedics
PURPOSE: The purpose of this study is to report on the use of Robotic-assisted total joint arthroplasty (RA-TJA) in China as well as the experience and expectations of Chinese doctors regarding this technology.

Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

Clinical neuroradiology
The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional spine imaging. In the last decades, the technological advancement, increasing availability and clinical success of CT led to a rapidly growing number ...

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...