AIMC Topic: Humans

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Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study.

BMC anesthesiology
BACKGROUND: Catheter-related bladder discomfort (CRBD) commonly occurs in patients who have indwelling urinary catheters while under general anesthesia. And moderate-to-severe CRBD can lead to significant adverse events and negatively impact patient ...

Automated gall bladder cancer detection using artificial gorilla troops optimizer with transfer learning on ultrasound images.

Scientific reports
The gallbladder (GB) is a small pouch and a deep tissue placed under the liver. GB Cancer (GBC) is a deadly illness that is complex to discover in an initial phase. Initial diagnosis can significantly enhance the existence rate. Non-ionizing energy, ...

Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.

Scientific reports
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks.

Scientific reports
A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus significantly affects the world's economic and health systems. Acute and chronic carrier phases play a crucial part in the spread of the HBV infectio...

Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.

JMIR formative research
BACKGROUND: The aging population and the shortage of geriatric care workers are major global concerns. Socially assistive robots (SARs) have the potential to address these issues, but developing SARs for various types of users is still in its infancy...

Regulating AI in Mental Health: Ethics of Care Perspective.

JMIR mental health
This article contends that the responsible artificial intelligence (AI) approach-which is the dominant ethics approach ruling most regulatory and ethical guidance-falls short because it overlooks the impact of AI on human relationships. Focusing only...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

Journal of orthopaedic surgery and research
PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there's only scarce evidence for measurable value in terms of patient outcomes, clinical ...

Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.

Neurosurgical review
Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly those under two years old, being more susceptible to skull fractures due to their unique physiological and developmental characteristics. A recent st...