AIMC Topic: Sexually Transmitted Diseases
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AI Chatbots as Sources of STD Information: A Study on Reliability and Readability.
Journal of medical systems
Apr 3, 2025
BACKGROUND: Artificial intelligence (AI) chatbots are increasingly used for medical inquiries, including sensitive topics like sexually transmitted diseases (STDs). However, concerns remain regarding the reliability and readability of the information...
Predicting the Risk of HIV Infection and Sexually Transmitted Diseases Among Men Who Have Sex With Men: Cross-Sectional Study Using Multiple Machine Learning Approaches.
Journal of medical Internet research
Feb 20, 2025
BACKGROUND: Men who have sex with men (MSM) are at high risk for HIV infection and sexually transmitted diseases (STDs). However, there is a lack of accurate and convenient tools to assess this risk.
STI/HIV risk prediction model development-A novel use of public data to forecast STIs/HIV risk for men who have sex with men.
Frontiers in public health
Jan 3, 2025
A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV risk prediction. Four machine learning methods, namely, Gradient Boosting Machine (GBM), Random Forest (RF), XG Boost, and Ensemble learning GBM-RF-XG...
Accuracy of symptom checker for the diagnosis of sexually transmitted infections using machine learning and Bayesian network algorithms.
BMC infectious diseases
Dec 18, 2024
BACKGROUND: A significant proportion of individuals with symptoms of sexually transmitted infection (STI) delay or avoid seeking healthcare, and digital diagnostic tools may prompt them to seek healthcare earlier. Unfortunately, none of the currently...
Preferences for attributes of an artificial intelligence-based risk assessment tool for HIV and sexually transmitted infections: a discrete choice experiment.
BMC public health
Nov 21, 2024
INTRODUCTION: Early detection and treatment of HIV and sexually transmitted infections (STIs) are crucial for effective control. We previously developed MySTIRisk, an artificial intelligence-based risk tool that predicts the risk of HIV and STIs. We ...
Qualitatively Assessing ChatGPT Responses to Frequently Asked Questions Regarding Sexually Transmitted Diseases.
Sexually transmitted diseases
Oct 31, 2024
BACKGROUND: ChatGPT, a large language model artificial intelligence platform that uses natural language processing, has seen its implementation across a number of sectors, notably in health care. However, there remains limited understanding regarding...
Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study.
Journal of medical Internet research
Sep 13, 2024
BACKGROUND: The 2022 global outbreak of mpox has significantly impacted health facilities, and necessitated additional infection prevention and control measures and alterations to clinic processes. Early identification of suspected mpox cases will as...
Fuzzy Logic: vulnerability of women who have sex with women to sexually transmitted infections.
Revista brasileira de enfermagem
Jul 29, 2024
OBJECTIVE: To describe the possibility of applying Fuzzy Logic in analyzing the vulnerability of Women Who Have Sex with Women to Sexually Transmitted Infections/HIV/AIDS.
Development of a Novel Fluorescent-Based Lateral Flow Assay for the Detection of Neisseria gonorrhoeae at the Point of Care.
Sexually transmitted diseases
Dec 19, 2023
BACKGROUND: Neisseria gonorrhoeae (NG) has acquired significant resistance, primarily due to extensive and unwarranted antibiotic utilization over several decades. This resistance has largely been associated with the syndromic management of sexually ...
Using Machine Learning to Identify Predictors of Sexually Transmitted Infections Over Time Among Young People Living With or at Risk for HIV Who Participated in ATN Protocols 147, 148, and 149.
Sexually transmitted diseases
Aug 16, 2023
BACKGROUND: Sexually transmitted infections (STIs) among youth aged 12 to 24 years have doubled in the last 13 years, accounting for 50% of STIs nationally. We need to identify predictors of STI among youth in urban HIV epicenters.
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