AI Medical Compendium Topic

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AI-powered prediction of HCC recurrence after surgical resection: Personalised intervention opportunities using patient-specific risk factors.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND: Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power o...

A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B.

Journal of hepatology
BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-...

Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset.

BMC infectious diseases
BACKGROUND: Predicting an individual's risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accur...

Human-AI collaboration improves adults' oral biomechanical functions: A multi-centre, self-controlled clinical trial.

Journal of dentistry
OBJECTIVES: Maintenance of oral muscle functions is important for survival and communication. Utilizing Artificial Intelligence (AI) as a self-health-management material has shown promise. Here we developed a functional and AI-enabled smartphone e-Or...

AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting antiviral treatment.

Journal of hepatology
BACKGROUND & AIMS: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, follow-up after sustained virological response (SVR) typically neglects the risk of liver-related events (LREs). This study in...

Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment.

Environment international
BACKGROUND: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monit...

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Molecular biology and evolution
Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancements, including the application of deep learning to overcome computational limitations, significant cha...

Promoting hand hygiene in a chemotherapy day center: the role of a robot.

Antimicrobial resistance and infection control
BACKGROUND: Hand hygiene is a critical component of infection prevention in healthcare settings. Innovative strategies are required to enhance hand hygiene practices among patients and healthcare workers (HCWs).

Artificial intelligence-based computer-aided diagnosis for breast cancer detection on digital mammography in Hong Kong.

Hong Kong medical journal = Xianggang yi xue za zhi
INTRODUCTION: Research concerning artificial intelligence in breast cancer detection has primarily focused on population screening. However, Hong Kong lacks a population-based screening programme. This study aimed to evaluate the potential of artific...

Using ChatGPT for medical education: the technical perspective.

BMC medical education
BACKGROUND: The chatbot application Bennie and the Chats was introduced due to the outbreak of COVID-19, which is aimed to provide substitution for teaching conventional clinical history-taking skills. It was implemented with DialogFlow with preset r...