AIMC Topic: Humans

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Artificial intelligence and deep learning algorithms for epigenetic sequence analysis: A review for epigeneticists and AI experts.

Computers in biology and medicine
Epigenetics encompasses mechanisms that can alter the expression of genes without changing the underlying genetic sequence. The epigenetic regulation of gene expression is initiated and sustained by several mechanisms such as DNA methylation, histone...

Evaluating machine learning model bias and racial disparities in non-small cell lung cancer using SEER registry data.

Health care management science
BACKGROUND: Despite decades of pursuing health equity, racial and ethnic disparities persist in healthcare in America. For cancer specifically, one of the leading observed disparities is worse mortality among non-Hispanic Black patients compared to n...

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

Neurology
BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific eff...

Enhancing SARS-CoV-2 Lineage Surveillance through the Integration of a Simple and Direct qPCR-Based Protocol Adaptation with Established Machine Learning Algorithms.

Analytical chemistry
Emerging and evolving Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) lineages, adapted to changing epidemiological conditions, present unprecedented challenges to global public health systems. Here, we introduce an adapted analytical ap...

Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

Journal of the American Heart Association
BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in ...

Artificial Intelligence and Radiologist Burnout.

JAMA network open
IMPORTANCE: Understanding the association of artificial intelligence (AI) with physician burnout is crucial for fostering a collaborative interactive environment between physicians and AI.

ARMNet: A Network for Image Dimensional Emotion Prediction Based on Affective Region Extraction and Multi-Channel Fusion.

Sensors (Basel, Switzerland)
Compared with discrete emotion space, image emotion analysis based on dimensional emotion space can more accurately represent fine-grained emotion. Meanwhile, this high-precision representation of emotion requires dimensional emotion prediction metho...

Edge Computing for AI-Based Brain MRI Applications: A Critical Evaluation of Real-Time Classification and Segmentation.

Sensors (Basel, Switzerland)
Medical imaging plays a pivotal role in diagnostic medicine with technologies like Magnetic Resonance Imagining (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), and ultrasound scans being widely used to assist radiologists and med...

Lower Limb Motion Recognition Based on sEMG and CNN-TL Fusion Model.

Sensors (Basel, Switzerland)
To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM...

Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure.

JAMA network open
IMPORTANCE: Serial functional status assessments are critical to heart failure (HF) management but are often described narratively in documentation, limiting their use in quality improvement or patient selection for clinical trials.