
Data augmentation alters feature importance in XGBoost for CVD prediction.
Data augmentation reshapes feature importance in CVD prediction models. Key findings: SMOTE model accuracy 1.0! ππ
Discover the newest research about AI innovations in π¦ Epidemiology.

Data augmentation reshapes feature importance in CVD prediction models. Key findings: SMOTE model accuracy 1.0! ππ

AI in CT Detection of COPD: 189 Publications, 37.83% Growth ππ

AI can enhance pandemic preparedness by analyzing diverse data sources for early pathogen detection. ππ

AI tools are aiding scientists in tracking disease origins and immune responses, enhancing treatment strategies. π§¬π

Machine learning predicts negative self-rated oral health in adults with 16.6% prevalence. Key predictors include socioeconomic status and anxiety. ππ¦·

Shared decision-making in radiology enhances patient care through leadership strategies and AI tools. Key findings from our review. ππ€

Machine learning fibrosis score for pediatric MASLD shows promise (AUROC 0.92) but requires caution and further validation. ππ©Ί

AI-designed multiepitope DNA vaccine shows promise against H5N1 clade 2.3.4.4b in chickens. π¦ π

Machine learning predicts cancer patient mortality dynamics, revealing three clinical patterns and key lab parameters. ππ‘

Lung lobe segmentation tools evaluated: TotalSegmentator excels, while data diversity enhances model accuracy. ππ«