AIMC Topic: Humans

Clear Filters Showing 30951 to 30960 of 95995 articles

Approaching expert-level accuracy for differentiating ACL tear types on MRI with deep learning.

Scientific reports
Treatment for anterior cruciate ligament (ACL) tears depends on the condition of the ligament. We aimed to identify different tear statuses from preoperative MRI using deep learning-based radiomics with sex and age. We reviewed 862 patients with preo...

Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina.

North Carolina medical journal
Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysf...

Artificial intelligence and the scientific method: How to cope with a complete oxymoron.

Clinics in dermatology
Artificial intelligence (AI) can be a powerful tool for data analysis, but it can also mislead investigators, due in part to a fundamental difference between classic data analysis and data analysis using AI. A more or less limited data set is analyze...

Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segment...

Enhancing Person Re-Identification Performance Through In Vivo Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This research investigates the potential of in vivo learning to enhance visual representation learning for image-based person re-identification (re-ID). Compared to traditional self-supervised learning (which require external data), the introduced in...

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization.

IEEE transactions on biomedical circuits and systems
For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are subjective, time-consuming, and labor-consuming. With the development of affective computing and Art...

CNN-based diagnosis model of children's bladder compliance using a single intravesical pressure signal.

Computer methods in biomechanics and biomedical engineering
Bladder compliance assessment is crucial for diagnosing bladder functional disorders, with urodynamic study (UDS) being the principal evaluation method. However, the application of UDS is intricate and time-consuming in children. So it'S necessary to...

Talking technology: exploring chatbots as a tool for cataract patient education.

Clinical & experimental optometry
CLINICAL RELEVANCE: Worldwide, millions suffer from cataracts, which impair vision and quality of life. Cataract education improves outcomes, satisfaction, and treatment adherence. Lack of health literacy, language and cultural barriers, personal pre...

Application of Hybrid DeepLearning Architectures for Identification of Individuals with Obsessive Compulsive Disorder Based on EEG Data.

Clinical EEG and neuroscience
Obsessive-compulsive disorder (OCD) is a highly common psychiatric disorder. The symptoms of this condition overlap and co-occur with those of other psychiatric illnesses, making diagnosis difficult. The availability of biomarkers could be useful fo...

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

European radiology
OBJECTIVES: To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of...