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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...

Development of a 5-Year Risk Prediction Model for Transition From Prediabetes to Diabetes Using Machine Learning: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Diabetes has emerged as a critical global public health crisis. Prediabetes, as the transitional phase with 5%-10% annual progression to diabetes, offers a critical window for intervention. The lack of a 5-year risk prediction model for d...

Binary classification of gynecological cancers based on ATR-FTIR spectroscopy and machine learning using urine samples.

Clinical and experimental medicine
Making an early diagnosis of cancer still in the early stages, when completely asymptomatic, is the challenge modern medicine has been setting for several decades. In gynecology, no effective screening has yet been found and approved for endometrial ...

Improving lower-extremity artery depiction and diagnostic confidence using dual-energy technique and popliteal artery monitoring in dual-low dose CT angiography.

Scientific reports
To assess the utility of dual-energy CT scanning (DECTs) with popliteal artery (PA) monitoring in dual low-dose (radiation and contrast) lower-extremity CT angiography (LE-CTA). 135 patients undergoing LE-CTA were prospectively included and divided i...

Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER) database.

Journal of orthopaedic surgery (Hong Kong)
The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has better overall performance than single computational approaches for clinical decision. The primary objective was to select prognostic variables and d...

The impact of AI feedback on the accuracy of diagnosis, decision switching and trust in radiography.

PloS one
Artificial intelligence decision support systems have been proposed to assist a struggling National Health Service (NHS) workforce in the United Kingdom. Its implementation in UK healthcare systems has been identified as a priority for deployment. Fe...

Artificial intelligence predicts pregnancy complications based on cytokine profiles.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
BACKGROUND: Early prediction of pregnancy complications is important for adequate and timely prevention, management, and reducing maternal/fetal pathogenesis.

Evidence of a social evaluation penalty for using AI.

Proceedings of the National Academy of Sciences of the United States of America
Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by other...

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 ...