AI Medical Compendium Topic

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Establishment of a risk prediction model for olfactory disorders in patients with transnasal pituitary tumors by machine learning.

Scientific reports
To construct a prediction model of olfactory dysfunction after transnasal sellar pituitary tumor resection based on machine learning algorithms. A cross-sectional study was conducted. From January to December 2022, 158 patients underwent transnasal s...

Using Google web search to analyze and evaluate the application of ChatGPT in femoroacetabular impingement syndrome.

Frontiers in public health
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT) is a new machine learning tool that allows patients to access health information online, specifically compared to Google, the most commonly used search engine in the United States. Patient...

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.

PloS one
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...

The Effect of Artificial Intelligence on Patient-Physician Trust: Cross-Sectional Vignette Study.

Journal of medical Internet research
BACKGROUND: Clinical decision support systems (CDSSs) based on routine care data, using artificial intelligence (AI), are increasingly being developed. Previous studies focused largely on the technical aspects of using AI, but the acceptability of th...

Development and evaluation of a deep learning framework for the diagnosis of malnutrition using a 3D facial points cloud: A cross-sectional study.

JPEN. Journal of parenteral and enteral nutrition
BACKGROUND: The feasibility of diagnosing malnutrition using facial features has been validated. A tool to integrate all facial features associated with malnutrition for disease screening is still demanded. This work aims to develop and evaluate a de...

Socio-demographic predictors of not having private dental insurance coverage: machine-learning algorithms may help identify the disadvantaged.

BMC public health
BACKGROUND: For accessing dental care in Canada, approximately 62% of the population has employment-based insurance, 6% have some publicly funded coverage, and 32% have to pay out-of pocket. Those with no insurance or public coverage find dental care...

A Comparative Review of Imaging Journal Policies for Use of AI in Manuscript Generation.

Academic radiology
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) technologies are rapidly evolving and offering new advances almost on a day-by-day basis, including various tools for manuscript generation and modification. On the other hand, these potentially ...

Deep Learning Method for Rapid Simultaneous Multistructure Temporal Bone Segmentation.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To develop and validate a deep learning algorithm for the automated segmentation of key temporal bone structures from clinical computed tomography (CT) data sets.