Artificial Intelligence Medical Compendium

BACKGROUND: The World Health Organization (WHO) has identified tuberculosis (TB) as the leading cause of death from a single infectious agent. False-positive rifampicin (RIF) resistance results from the Xpert MTB/RIF Ultra assay are common in TB pati... read more 

The potential leakage of training data privacy in deep learning has been a topic of concern for researchers and the public. To provide formal and rigorous privacy guarantees, many learning systems integrate differential privacy (DP) with SGD optimize... read more 

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that affects multiple brain systems. Altered brain function can be observed through resting-state functional magnetic resonance imaging (rs-fMRI). While machine lear... read more 

Time series forecasting has seen extensive application including traffic and energy. Time series data often contain complex patterns and noise, posing challenges for deep learning models to effectively extract features and achieve accurate forecastin... read more 

Accurate segmentation of abdominal organs in Computed Tomography (CT) scans is crucial for effective lesion diagnosis, radiotherapy planning, and patient follow-up. Although deep learning has shown great performance with fully supervised learning, it... read more 

Most graph-based multi-view clustering methods first learn individual similarity graphs for each view and then derive a consensus graph from these similarity graphs. However, these methods suffer from several limitations, such as irreversible informa... read more 

Advances in artificial intelligence are enabling flexible intelligent sensors with performance rivaling or surpassing human perception. In this work, we have introduced a dual-mode capacitive sensor featuring double-sided microtetrahedral electrodes ... read more 

Hearing loss affects approximately two thirds of adults in the United States aged 70 years or older and frequently remains untreated despite its well-documented harms, including accelerated cognitive decline, increased caregiver burden, and higher he... read more 

BACKGROUND: Non-linear equine electrocardiography (ECG) analysis is an actively developing study area which has the potential to lead to novel, artificial intelligence-based diagnostic tools in equine cardiology. As more ECG recording devices are bec... read more 

Language disturbances are central features of serious mental illnesses, yet traditional clinical assessments often rely on subjective evaluation that may overlook subtle speech anomalies. This study employs natural language processing (NLP) to object... read more