AIMC Topic: Aged

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Pioneering artificial intelligence-based real time assistance for intracranial liquid embolization in humans: an initial experience.

Journal of neurointerventional surgery
BACKGROUND: Liquid embolization in neuroendovascular procedures carries the risk of embolizing an inappropriate vessel. Operators must pay close attention to multiple vessels during the procedure to avoid ischemic complications. We report our experie...

Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.

Journal of neurointerventional surgery
BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians.

First-in-human, real-time artificial intelligence assisted cerebral aneurysm coiling: a preliminary experience.

Journal of neurointerventional surgery
BACKGROUND: Neuroendovascular procedures require careful and simultaneous attention to multiple devices on multiple screens. Overlooking unintended device movements can result in complications. Advancements in artificial intelligence (AI) have enable...

OCT in dermatology: a process for determining whether a fully diversified dataset is needed for AI model-building.

Optics letters
Optical coherence tomography (OCT) has sufficient depth penetration for detection of skin pathologies, but its detection effectiveness can be aided by the assistance of artificial intelligence (AI) modeling. AI model-building identifies pathologies b...

A machine learning approach for assessing acute infection by erythrocyte sedimentation rate (ESR) kinetics.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: The erythrocyte sedimentation rate (ESR) is a traditional marker of inflammation, valued for its simplicity and low cost but limited by unsatisfactory specificity and sensitivity. This study evaluated the equivalence of ESR measurements o...

Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates.

Neurobiology of disease
BACKGROUND: Despite prior studies on early-stage Parkinson's disease (PD) brain connectivity and temporal patterns, differences between tremor-dominant (TD) and postural instability/gait difficulty (PIGD) motor subtypes remain poorly understood. Our ...

Developing an interpretable machine learning model for screening depression in older adults with functional disability.

Journal of affective disorders
This study utilized data from the 2020 wave of the China Health and Retirement Longitudinal Study database, selecting 4322 participants aged 60 and above as the study sample. Important predictors of depression in older adults with functional disabili...

A deep learning model could screen for coronary heart disease from a "pseudo-normal" electrocardiogram.

Medicine
BACKGROUND: This study aimed to develop a deep learning model (DLM) for rapid screening of coronary heart disease (CHD) using "pseudo-normal" electrocardiograms (ECGs), particularly focusing on patients who present with normal or near-normal ECGs at ...

Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis.

Journal of medical Internet research
BACKGROUND: Although robots have emerged as a new means of delivering health information, with the advancement of artificial intelligence technology, individuals still face challenges in deciding whether to trust the health information provided by th...