AI Medical Compendium Topic:
Cross-Sectional Studies

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Identification and Optimization of Contributing Factors for Precocious Puberty by Machine/Deep Learning Methods in Chinese Girls.

Frontiers in endocrinology
BACKGROUND AND OBJECTIVES: As the worldwide secular trends are toward earlier puberty, identification of contributing factors for precocious puberty is critical. We aimed to identify and optimize contributing factors responsible for onset of precocio...

Nurse preferences of caring robots: A conjoint experiment to explore most valued robot features.

Nursing open
AIM: Due to the COVID pandemic and technological innovation, robots gain increasing role in nursing services. While studies investigated negative attitudes of nurses towards robots, we lack an understanding of nurses' preferences about robot characte...

An insight into the current perceptions of UK radiographers on the future impact of AI on the profession: A cross-sectional survey.

Journal of medical imaging and radiation sciences
INTRODUCTION: As a profession, radiographers have always been keen on adapting and integrating new technologies. The increasing integration of artificial intelligence (AI) into clinical practice in the last five years has been met with scepticism by ...

Application of the deep learning algorithm in nutrition research - using serum pyridoxal 5'-phosphate as an example.

Nutrition journal
BACKGROUND: Multivariable linear regression (MLR) models were previously used to predict serum pyridoxal 5'-phosphate (PLP) concentration, the active coenzyme form of vitamin B6, but with low predictability. We developed a deep learning algorithm (DL...

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome.

Sovremennye tekhnologii v meditsine
Currently, software products for use in medicine are actively developed. Among them, the dominant share belongs to clinical decision support systems (CDSS), which can be intelligent (based on mathematical models obtained by machine learning methods o...

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

European radiology
OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed ...

Digital Health Profile of South Korea: A Cross Sectional Study.

International journal of environmental research and public health
(1) Backgroud: For future national digital healthcare policy development, it is vital to collect baseline data on the infrastructure and services of medical institutions' information and communication technology (ICT). To assess the state of medical ...

Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques.

Endocrine
OBJECTIVES: We adopted the machine-learning algorithms and deep-learning sequential model to determine and optimize most important factors for overweight and obesity in Chinese preschool-aged children.

Assessing the potentiality of algorithms and artificial intelligence adoption to disrupt patient primary care with a safer and faster medication management: a systematic review protocol.

BMJ open
INTRODUCTION: In primary care, almost 75% of outpatient visits by family doctors and general practitioners involve continuation or initiation of drug therapy. Due to the enormous amount of drugs used by outpatients in unmonitored situations, the pote...