AIMC Topic: Humans

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Predicting patient deterioration with physiological data using AI: systematic review protocol.

BMJ health & care informatics
INTRODUCTION: The second iteration of the National Early Warning Score has been adopted widely within the UK and internationally. It uses routinely collected physiological measurements to standardise the assessment and response to acute illness. Its ...

Digitally Enabled AI-Interpreted Salivary Ferning-Based Ovulation Prediction: Feasibility Study.

Journal of medical Internet research
BACKGROUND: Females with irregular or unpredictable cycles, including those with polycystic ovary syndrome (PCOS), have limited options for validated at-home ovulation prediction. The majority of over-the-counter ovulation prediction kits use urinary...

Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint.

Journal of medical Internet research
Digital twin (DT) technology is revolutionizing clinical practice by integrating diverse epidemiological data sources to create dynamic, patient-specific simulations. By leveraging data from genomics, proteomics, imaging, sociodemographics, and real-...

Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review.

JMIR mental health
BACKGROUND: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GISs) ...

Innovative machine learning approach for liver fibrosis and disease severity evaluation in MAFLD patients using MRI fat content analysis.

Clinical and experimental medicine
This study employed machine learning models to quantitatively analyze liver fat content from MRI images for the evaluation of liver fibrosis and disease severity in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). A total o...

Next-gen vision: a systematic review on robotics transforming ophthalmic surgery.

Journal of robotic surgery
Robotics in ophthalmic surgery marks a major advancement in surgical accuracy, safety, and therapeutic outcomes. This systematic review evaluates the evolution, current clinical applications, and future prospects of robotic systems in ophthalmology. ...

Retinal image-based disease classification using hybrid deep architecture with improved image features.

International ophthalmology
OBJECTIVE: Ophthalmologists use retinal fundus imaging as a useful tool to diagnose retinal issues. Recently, research on machine learning has concentrated on disease diagnosis. However, disease detection is less accurate, more likely to be misidenti...

Automated classification of skeletal malocclusion in German orthodontic patients.

Clinical oral investigations
OBJECTIVES: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differen...

Bioinformatics analysis of Rho-signal transduction genes in postmenopausal osteoporosis and periodontitis.

Scientific reports
Postmenopausal osteoporosis (PMOP) increases the risk of periodontitis (PD), yet the shared mechanisms remain unclear. Rho-signal transduction genes may play a role due to their involvement in bone remodeling. This study aimed to explore Rho-related ...

Machine learning enables legal risk assessment in internet healthcare using HIPAA data.

Scientific reports
This study explores how artificial intelligence technologies can enhance the regulatory capacity for legal risks in internet healthcare based on a machine learning (ML) analytical framework and utilizes data from the health insurance portability and ...