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Automatic segmentation of male pelvic floor soft tissue structures for anatomical simulation and morphological assessment in lower rectal cancer surgery.

Techniques in coloproctology
BACKGROUND: Pelvic anatomy is a complex network of organs that varies between individuals. Understanding the anatomy of individual patients is crucial for precise rectal cancer surgeries. Therefore, developing technology that can allow visualization ...

Virtual contrast-enhanced maximum intensity projections from high-b-value diffusion-weighted breast MRI: a feasibility study.

European radiology experimental
BACKGROUND: Maximum intensity projections (MIPs) facilitate rapid lesion detection both for contrast-enhanced (CE) and diffusion-weighted imaging (DWI) breast magnetic resonance imaging (MRI). We evaluated the feasibility of AI-based virtual CE subtr...

Construction and application of machine learning models for predicting intradialytic hypotension.

PloS one
INTRODUCTION: Intradialytic hypotension (IDH) remains a prevalent complication of hemodialysis, which is associated with adverse outcomes for patients. This study seeks to harness machine learning to construct predictive models for IDH based on multi...

Translation and validation of the artificial intelligence anxiety scale in German.

PloS one
AIM: Artificial intelligence anxiety refers to fear due to challenges caused by AI-related changes in one's own life. As the first study, our aim was to translate and validate the German version of the Artificial Intelligence Anxiety Scale (AIAS-G). ...

Artificial intelligence-assisted ultrasound screening for breast cancer in China: a prospective, clustered, controlled, population-based study.

Breast cancer research : BCR
INTRODUCTION: Breast cancer Mammography (MAM) screening was proven to improve survival worldwide. However, younger patients with higher breast density made MAM less effective in China. It is necessary to establish Chinese-specific effective screening...

Anston attentional network for structured data based stroke risk prediction in smart aging.

Scientific reports
To reduce the pressure on public health services caused by the aging population, nursing homes need to predict disease risks for the elderly periodically. To improve the disease risks predicting ability of nursing homes, we designed Anston (An Attent...

Machine learning approaches overcome imbalanced clinical data for intraoral free flap monitoring.

Scientific reports
Free flap reconstruction is essential for treating intraoral defects; however, failure can lead to complex and prolonged complications. While various monitoring methods have been employed to prevent such situations, they are qualitative and sometimes...

Evolving Health Information-Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol.

Journal of medical Internet research
BACKGROUND: Online health information seeking is undergoing a major shift with the advent of artificial intelligence (AI)-powered technologies such as voice assistants and large language models (LLMs). While existing health information-seeking behavi...

Cardiovascular risk prediction and influencing predictors identification among Bangladeshi individuals using machine learning algorithms and association rule mining.

PloS one
BACKGROUND: Cardiovascular disease (CVD) encompasses a group of disorders that affect the heart and blood vessels, making it one of the leading causes of death globally, including in Bangladesh. Applying predictive modeling for the early identificati...

Estimated glucose disposal rate predicts frailty through diabetes: Evidence from machine learning and mediation models in NHANES.

PloS one
OBJECTIVE: As an emerging insulin resistance marker, the relationship between estimated glucose disposal rate (eGDR) and frailty needs further exploration. This study examines the eGDR-frailty link, develops a machine learning predictive model to add...