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A machine learning-enhanced gastric cancer diagnostic method based on shell-isolated nanoparticle-enhanced Raman spectroscopy.

Nanoscale
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...

Road traffic injuries (RTIs) in children and adolescents in India: an overview of epidemiology, reported reasons and its implications.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: Road traffic injuries (RTIs) rank among the top causes of mortality and disability in children and adolescents, resulting in substantial socioeconomic impacts.

Cross-modal fusion of brain imaging and clinical data for Parkinson's disease progression prediction.

PloS one
BACKGROUND: Machine learning shows great potential in science but struggles with complex, high-dimensional multi-omics data. PD progression is long, diagnosed mainly by clinical signs. This paper proposes a novel decision fusion method to improve the...

Albumin-corrected anion gap as a predictor of 28-day mortality in acute respiratory distress syndrome: A machine learning-based retrospective study.

PloS one
BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) remains a critical condition associated with high mortality rates, prolonged hospitalization, and reduced quality of life despite advances in critical care. The albumin-corrected anion gap (ACAG)...

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...

Reducing Artifact Preprocessing in Heart Rate Variability-Based Personalized Psychosis Prediction Using Adaptive Long Short-Term Memory Models.

International journal of neural systems
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...

AI-driven discovery of dual antiaging and anti-AD therapeutics via PROTAC target deconvolution of a super-enhancer-regulated axis.

Science advances
The lack of safe, durable therapeutics that act against both biological aging and Alzheimer's disease is an unmet clinical need. To bridge this gap, we devised an artificial intelligence (AI)-enabled approach that pairs rapid compound triage with mec...

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...