AIMC Topic: Machine Learning

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Machine learning-assisted multicolor identification and quantification of antidepressant drugs by waste-derived fluorescent nanoprobes: Towards green AI-based electronic tongue.

Analytica chimica acta
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...

Predicting cyanobacteria removal efficiency in flocculation-DAF: Improving interpretable automated machine learning with CVAE data augmentation.

Water research
Flocculation-dissolved air flotation (DAF) is an efficient and widely adopted technique for cyanobacteria separation. However, optimizing its removal efficiency remains challenging due to complex interdependencies among water quality, cyanobacterial ...

Identification of the core genes KLRB1 and RETN as potential shared diagnostic markers for major depressive disorder and systemic lupus erythematosus through bioinformatics and machine learning methodologies.

Journal of neuroimmunology
This study investigates the shared molecular mechanisms between major depressive disorder (MDD) and systemic lupus erythematosus (SLE) through integrated bioinformatics analysis. Analysis of multiple GEO datasets identified 23 common differentially e...

A global analysis of the influence of shallow and deep groundwater tables on relationships between environmental parameters and heatwaves.

Environmental research
Heatwaves increasingly impact ecosystems, human health, and economic activities worldwide. As their frequency and intensity rise, understanding the mechanisms driving heatwave dynamics and interactions with land surface processes becomes crucial. Whi...

Construction of a Minimal Sensor Array Using Fingerprint Protein Corona on Nanostars for Detecting Protein Isoforms and Disease States.

ACS nano
Signature-based protein detection coupled with machine learning algorithms has revolutionized traditional sensing methods, providing rapid, inexpensive, and selectivity-driven detection without the use of specialized equipment. This strategy leverage...

The role of IRF-1 in mediating T-cell immune imbalance in systemic lupus erythematosus and the construction of a diagnostic model.

Autoimmunity
Systemic lupus erythematosus (SLE), characterized by immune dysregulation, urgently requires improved diagnostic tools and mechanistic insights. The role of interferon regulatory factor-1 (IRF-1) remains unclear. We integrated single-cell transcripto...

Systematic review and comparison of machine learning and conventional statistical models for predicting cardiovascular events in dialysis patients.

Renal failure
This systematic review aimed to evaluate the performance of machine learning (ML) models and conventional statistical models (CSMs) for predicting cardiovascular events in dialysis patients. Following PRISMA guidelines, eligible studies were searched...

Plasma metabolomics disentangles T2DM- and CAD-specific dysmetabolism and identifies potential biomarkers for CAD risk escalation in diabetic patients.

Cardiovascular diabetology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major driver of coronary artery disease (CAD). Prior studies often conflate T2DM- and CAD-specific metabolic alterations, limiting insights into CAD pathogenesis in T2DM. This study aimed to distinguis...

The ADVANCE toolkit: Automated descriptive video annotation in naturalistic child environments.

Behavior research methods
Video recordings are commonplace for observing human and animal behaviours, including interindividual interactions. In studies of humans, analyses for clinical applications remain particularly cumbersome, requiring human-based annotation that is time...

The Magic Curiosity Arousing Tricks (MagicCATs) database in Italian younger and middle-aged adults: Descriptive statistics and rule-based machine learning.

Behavior research methods
Epistemic emotions, and in particular curiosity, seem to enhance memory for both the specific information that stimulates the individual's curiosity and information presented in close temporal proximity. Most studies on memory and curiosity have adop...