Artificial Intelligence Medical Compendium

Graph neural networks (GNNs) have shown potential in analyzing brain functional networks for neuropsychiatric disorder diagnosis, yet existing GNN-based methods for attention-deficit/hyperactivity disorder (ADHD) identification face accuracy limitati... read more 

Surface-enhanced Raman scattering (SERS) technology, with its single-molecule detection capability and molecular specificity, has become a cornerstone of biomedical diagnosis. Recent advances in stimuli-responsive SERS nanoprobes extend its role beyo... read more 

OBJECTIVE: To identify the most influential features of asthma control in children and to assess whether feature selection improves model performance. METHODS: Records of 890 patients (<18 years) from the Immunology, Asthma, and Allergy Research Inst... read more 

Sepsis-associated encephalopathy (SAE) is a common and serious complication of sepsis that leads to acute brain dysfunction and long-term cognitive impairment. We used widely targeted LC-MS/MS plasma metabolomics in 29 healthy controls, 32 sepsis pat... read more 

As predictive analytics become more widely integrated into local public health responses to the United States overdose epidemic, community-based substance use service providers have begun to adopt machine learning-based predictive tools to guide the ... read more 

A fully automated continuous flow synthesizer for diblock copolymer (BCP) synthesis was constructed comprising elements of flow chemistry, automation, machine learning and in-line monitoring. A new method using in-line FTIR spectroscopic analysis for... read more 

Organoid platforms have reshaped in vitro human biology yet remain constrained by batch variability, sparse longitudinal readouts and barriers to scale. This review introduces Artificial Intelligence Virtual Organoids (AIVOs), also termed silicon org... read more 

Jasmine essential oil holds significant importance in fragrance and food industries due to its unique aroma and bioactivity. However, traditional extraction processes suffer from low yields and severe flavor losses. This study employed flavoromics an... read more 

Bipolar disorder (BD) and major depressive disorder (MDD) are highly prevalent, disabling psychiatric illnesses marked by substantial heterogeneity and frequent metabolic and inflammatory comorbidities. Growing evidence implicates low-grade inflammat... read more 

Mass-based material flow compositions (MFCOs) are among the most relevant indicators for the quality of sorting processes in waste management. They provide the basis for the assessment and improvement of the purity and yield of material streams. Whil... read more