FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
C&EN

Enhancing Engine Performance and Sustainability: Gold Nanoparticles and Machine Learning for Biodiesel Optimization in Compression Ignition Systems

Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...
Scientific Research Publishing

Natekin, A. and Knoll, A. (2013) Gradient Boosting Machines, a Tutorial. Frontiers in Neurorobotics, 7, Article 21.

ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.
IEEE

Gradient Boosting Decision Trees on Medical Diagnosis Over Tabular Data

Abstract: Medical diagnosis is a crucial task in the medical field, in terms of providing accurate classification and respective treatments. Having near-precise decisions based on correct diagnosis ...
GitHub

Stochastic gradient-boosted decision trees for multivariate classification, usable standalone and via Python interface.

Check the paper on ArXiv: FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Stochastic gradient-boosted ...
Frontiers

A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network

Reproductive toxicity is a concern critical to human health and chemical safety assessment. Recently, the U.S. Food and Drug Administration announced plans to assess toxicity with artificial ...
Scientific Research Publishing

MLP, XGBoost, KAN, TDNN, and LSTM-GRU Hybrid RNN with Attention for SPX & NDX European Call Option Pricing ()

1 Fu Foundation School of Engineering and Applied Science, Columbia University, New York, USA. 2 Recognition Technologies, Inc., New York, USA. We explore the performance of various artificial neural ...
jnis.bmj

Development and validation of an explainable machine learning prediction model for futile recanalization after mechanical thrombectomy in acute large vessel occlusion stroke

Background Mechanical thrombectomy (MT) is the primary treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). However, the likelihood of futile recanalization (FR) at 90 ...