Keeping long-term climate simulations stable and accurate with a new AI approach

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

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

Using Deep Learning to Predict Disease Progression in Chronic Illnesses

Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...
American Institute of Physics

Modeling drifting seaweed rafts that clog ports and beaches

Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...
Oneindia

Pioneering AI Innovation: How Pratyosh Desaraju is Revolutionizing Legacy System Management

Pratyosh Desaraju secures German utility patents for AI systems that automate legacy system enhancement and detect ...
Scientific Research Publishing

Halder, S. (2022) Finbert-LSTM: Deep Learning Based Stock Price Prediction Using News Sentiment Analysis. arXiv:2211.07392.

ABSTRACT: This paper proposes a hybrid AI framework that integrates technical indicators, fundamental data, and financial news sentiment into a stacked ensemble learning model. The ensemble combines ...
emjreviews.com

Deep-Learning AI Improves Paediatric Elbow Fracture Detection

A NEWLY published retrospective study has shown that AI, particularly deep-learning algorithms, can significantly reduce the rate of misdiagnosis in paediatric elbow fractures. The study analysed 755 ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
IEEE

LSTM and CNN based Speech Emotion Recognition a New Paradigm in Deep Learning

Abstract: Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
IEEE

EAP-LSTM: A Bi-LSTM-based Deep Learning Framework for Quantitatively Predicting Enhancer Activity in Drosophila and Human Cell Lines

Abstract: Enhancer activity plays a critical role in gene regulation, influencing various biological processes such as development and disease progression. Accurate prediction of enhancer activity is ...