Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

2 clinical studies listed.

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Gender Prediction

Tundra lists 2 Gender Prediction clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

This data is also available as a public JSON API. AI systems and LLMs are encouraged to use it for structured queries.

NOT YET RECRUITING

NCT07886086

Comparison of Escape Room and Branching Scenario Games in Nursing Education

The aim of this study is to examine the effects of a web-based escape room (EQUITY-ROOM) and a web-based branching scenario (EQUITY-PATH) simulation added to standardized video-based education on nursing students' gender perception, dating violence myths, and dating violence attitudes.The study is designed as a 3-arm pretest-posttest parallel randomized controlled trial. Participants (3rd-year nursing students, N=72) will be randomly allocated to three groups in a 1:1:1 ratio: 1. EQUITY-ROOM Group: Standardized video-based education + Web-based Escape Room Game 2. EQUITY-PATH Group: Standardized video-based education + Web-based Branching Scenario GameActive 3. Control Group: Standardized video-based education onlyPrimary outcome is attitudes toward dating violence, while gender perception and dating violence myths serve as secondary outcomes. Outcome measures will be evaluated before the intervention (pretest) and one week after the intervention (posttest).

Gender: All

Ages: 18 Years - Any

Updated: 2026-10-21

Gender Prediction
Dating Violence
Nursing Education
RECRUITING

NCT07726290

Validating AI for Gender Prediction Using Morphometric Analysis of the Mandible

This retrospective validity study evaluates the accuracy of artificial intelligence (AI) in determining gender from mandibular morphometric linear measurements. The study utilizes pre-existing Cone Beam Computed Tomography (CBCT) scans of adult Egyptian dental patients. After automatic segmentation of the mandible from these scans, a radiologist will manually perform measurements from certain anatomical points. These measurements will be the reference standard for the AI models. A three-dimensional deep learning model will be developed to perform two tasks: 1. To identify the anatomical points and make the specified linear measurements from these points on the segmented mandibles 2. To accurately predict gender based on these measurements. (Main Objective) The primary objective of this study is to evaluate the accuracy of machine learning algorithms in gender identification from linear morphometric measurements of the mandible. The known gender from patient records will serve as the reference standard. This study will assess the reliability of AI as an objective tool for gender determination for forensic purposes.

Gender: All

Ages: 18 Years - Any

Updated: 2026-07-24

Gender
MANDIBLE
Forensic Dentistry
+3