AIMC Topic: Humans

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An anxiety screening framework integrating multimodal data and graph node correlation.

Artificial intelligence in medicine
Anxiety disorders are a significant global health concern, profoundly impacting patients' lives and social functioning while imposing considerable burdens on families and economies. However, current anxiety screening methods face limitations due to c...

Linear and nonlinear features of EEG microstate associated with insomnia.

Sleep medicine
BACKGROUND: Numerous studies have revealed abnormalities in EEG microstate in insomnia, primarily quantified using linear features, whereas nonlinear metrics remain underexplored. This study aimed to compare linear and nonlinear features and further ...

The value of a deep learning image reconstruction algorithm for assessing vertebral compression fractures using dual-energy computed tomography.

European journal of radiology
PURPOSE: To evaluate the value of deep learning image reconstruction (DLIR) in improving image quality of virtual non-hydroxyapatite (VNHAP) and virtual monoenergetic images (VMIs), and radiologists' performance in detecting acute vertebral compressi...

Classification of glioma grade and Ki-67 level prediction in MRI data: A SHAP-driven interpretation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study focuses on artificial intelligence-driven classification of glioma and Ki-67 leveling using T2w-FLAIR MRI, exploring the association of Ki-67 biomarkers with deep learning (DL) features through explainable artificial intelligence (XAI) and...

Machine learning strategies for multi-label pre-diagnosis of diseases with superficial data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: General practice (GP) pre-diagnosis, a key task in disease triage, directs patients to suitable departments despite limited data and multi-label classification challenges. To address this issue, a framework with dimensionali...

Appropriateness of acute breast symptom recommendations provided by ChatGPT.

Clinical imaging
PURPOSE: We evaluated the accuracy of ChatGPT-3.5's responses to common questions regarding acute breast symptoms and explored whether using lay language, as opposed to medical language, affected the accuracy of the responses.

VAE-GANMDA: A microbe-drug association prediction model integrating variational autoencoders and generative adversarial networks.

Artificial intelligence in medicine
Traditional biological experimental methods typically require weeks or even months of experimentation, and the cost of each experiment can reach hundreds or even thousands of dollars, which is quite expensive and time-consuming. To address this, a mo...

Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.

ACS nano
Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this work, utilizing anaerobic bacteria capable of seeking out hypoxic areas for flourishing, we constructed...

Magnetic-Driven Hydrogel Robots Loaded with Mitomycin for Active Therapy of Bladder Cancer.

ACS applied materials & interfaces
Intravesical drug instillation is a common treatment for bladder cancer, but it suffers from poor targeting and suboptimal patient experience due to the influence of gravity. Here, we innovatively designed a bladder cancer treatment method using sodi...

Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast ...