Artificial Intelligence Medical Compendium

Discovering differentially expressed genes (DEGs) is an essential process for diagnosis and treatment. In this study, we evaluate the capacity of machine learning algorithms to identify genes that are simulated as truly differentially expressed. We f... read more 

Ammonium (NH4 +) pollution in wastewater poses severe ecological and health risks. This study introduces a magnetic biochar composite (SB@MFO) synthesized from sugarcane bagasse and MnFe2O4 for efficient NH4 + removal. The composite exhibits a mesopo... read more 

Maple syrup quality evaluation involves multiple parameters, including color classification, flavor assessment, and the measurement of sugar concentration, which are influenced by the complex chemical composition of the syrup matrix. Conventional qua... read more 

Volumetric meta-optics have emerged as a compact high-performance platform for advanced imaging, color routing in image sensors, and on-chip wavefront control. Realizing such devices depends on solving a high-dimensional nonconvex inverse-design prob... read more 

Antimicrobial resistance (AMR) in Staphylococcus aureus (S. aureus) poses a serious global health threat, undermining treatment outcomes and necessitating the development of innovative therapeutic strategies. Methicillin-resistant Staphylococcus aure... read more 

MOTIVATION: Effective computational tool development depends on our ability to measure progress with rigorous benchmarking, allowing developers to showcase advances and users to select the best of the available options. Computational biology has deve... read more 

PURPOSE: Reliable decoding of lower-limb motor intent from surface electromyography signals remains challenging due to electrode placement variability, muscle fatigue, inter-subject differences, and differences between able-bodied and amputee populat... read more 

For the past seven decades, radiation-induced esophagitis (RE) has been a major dose-limiting acute toxicity of thoracic radiotherapy, substantially impairing patients' quality of life and their ability to complete planned treatment courses. Research... read more 

Anxiety-induced motion artifacts frequently compromise image quality during non-sedated cardiac magnetic resonance imaging (CMR), leading to rescans and increased healthcare burdens. This retrospective cohort study hypothesized that combining multidi... read more 

The performance of many facial recognition (FR) algorithms is adversely affected in uncontrolled settings due to diverse facial expressions, lighting changes, occlusions, and image noise. This poses a significant challenge in developing a reliable an... read more