AI Medical Compendium Topic

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Cross-Sectional Studies

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Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study.

BMC oral health
BACKGROUND: Oral mucosal lesions are widespread globally, have a high prevalence in clinical practice, and significantly impact patients' quality of life. However, their pathogenesis remains unclear. Recent evidences suggested that hematological para...

Anti-HBs persistence and anamnestic response among medical interns vaccinated in infancy.

Scientific reports
Medical interns are at high risk of acquiring Hepatitis B Virus (HBV) infection during their training. HBV vaccination is the most effective measure to reduce the global incidence of HBV. The duration of protection after HBV vaccination is still cont...

Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.

BMJ open
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...

AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows.

BMC medical education
BACKGROUND: Artificial Intelligence (AI) is transforming medical education globally, offering solutions to challenges such as resource limitations and limited clinical exposure. However, its integration in resource-constrained settings like Palestine...

Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus.

Scientific reports
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...

Global Health care Professionals' Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study.

JMIR medical education
BACKGROUND: ChatGPT is a large language model-based chatbot developed by OpenAI. ChatGPT has many potential applications to health care, including enhanced diagnostic accuracy and efficiency, improved treatment planning, and better patient outcomes. ...

Machine learning approach for unmet medical needs among middle-aged adults in South Korea: a cross-sectional study.

BMC health services research
BACKGROUND: South Korea is reported to have higher levels of unmet medical needs (UMN) than other countries, particularly among the middle-aged adult population. Considering that this group constitutes a substantial portion of the country's productiv...

The role of AI in reducing maternal mortality: Current impacts and future potentials: Protocol for an analytical cross-sectional study.

PloS one
BACKGROUND: Maternal and newborn mortality remains a critical public health challenge, particularly in resource-limited settings. Despite global efforts, Kenya continues to report high maternal mortality rates of over 350 deaths per 100,000 live birt...

Professional identity and its relationships with AI readiness and interprofessional collaboration.

PloS one
BACKGROUND: In contemporary healthcare practices, the convergence of Artificial Intelligence (AI) and interprofessional collaboration represents a transformative era marked by unprecedented opportunities and challenges. The introduction of AI technol...