AIMC Topic: Humans

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Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

The American journal of cardiology
Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alternatives like left atrial appendage closure devices lower stroke risk with fewer nonprocedural blee...

Fostering Informed Consent and Shared Decision-Making in Maternity Nursing With the Advancement of Artificial Intelligence.

MCN. The American journal of maternal child nursing
Artificial intelligence (AI), defined as algorithms built to reproduce human behavior, has various applications in health care such as risk prediction, medical image classification, text analysis, and complex disease diagnosis. Due to the increasing ...

Fast screening of COVID-19 inpatient samples by integrating machine learning and label-free SERS methods.

Analytica chimica acta
BACKGROUND: Advances in bio-analyte detection demonstrate the need for innovation to overcome the limitations of traditional methods. Emerging viruses evolve into variants, driving the need for fast screening to minimize the time required for positiv...

Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-reading workload if used as a first-reader, ruling-out negative CT-scans at baseline. Evidence is lacking to support AI performance when compared to gol...

Interpretable modality-specific and interactive graph convolutional network on brain functional and structural connectomes.

Medical image analysis
Both brain functional connectivity (FC) and structural connectivity (SC) provide distinct neural mechanisms for cognition and neurological disease. In addition, interactions between SC and FC within distributed association regions are related to alte...

Exploring the values underlying machine learning research in medical image analysis.

Medical image analysis
Machine learning has emerged as a crucial tool for medical image analysis, largely due to recent developments in deep artificial neural networks addressing numerous, diverse clinical problems. As with any conceptual tool, the effective use of machine...

Applications of Artificial Intelligence in Neurosurgery for Improving Outcomes Through Diagnostics, Predictive Tools, and Resident Education.

World neurosurgery
BACKGROUND: Artificial intelligence (AI) has become an increasingly prominent tool in the field of neurosurgery, revolutionizing various aspects of patient care and surgical practices. AI-powered systems can provide real-time feedback to surgeons, en...

Exploring temporal information dynamics in Spiking Neural Networks: Fast Temporal Efficient Training.

Journal of neuroscience methods
BACKGROUND: Spiking Neural Networks (SNNs) hold significant potential in brain simulation and temporal data processing. While recent research has focused on developing neuron models and leveraging temporal dynamics to enhance performance, there is a ...

AI in Breast Cancer Imaging: An Update and Future Trends.

Seminars in nuclear medicine
Breast cancer is one of the most common types of cancer affecting women worldwide. Artificial intelligence (AI) is transforming breast cancer imaging by enhancing diagnostic capabilities across multiple imaging modalities including mammography, digit...

Artificial Intelligence Based Augmented Reality Navigation in Minimally Invasive Partial Nephrectomy.

Urology
OBJECTIVE: To explore the role of artificial intelligence based augmented reality intraoperative real-time navigation in minimally invasive partial nephrectomy to standardize renal hilum dissection procedures and improve operative efficiency.