Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

According to Andrej Karpathy on Twitter, the Python random.seed() function produces identical random number generator (RNG) streams when seeded with positive and negative integers of the same ...

Here's the complete project structure: decision-trees-random-forest_from_scratch_probabilistic-classifier/ │ ├── data/ │ ├── raw/ │ └── processed/ │ ├── src/ │ ├── utils/ │ │ ├── data_split.py │ │ ├── ...

Background: Heart failure (HF), with its distinct phenotypes, poses significant public health challenges. Early diagnosis of specific HF phenotypes is crucial for timely therapeutic intervention.

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior ...

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...

Abstract: This work explores the Random Forest classifier's effectiveness in analyzing healthcare data for predicting stroke risks. In this study, data preprocessing is done intensively, which ranges ...