Machine-learning immune-system analysis study may hold clues to personalized medicine

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by ...

AI cancer tools may rely on 'shortcut learning' rather than genuine biological signals

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...

AI Stock Trading: The Future of Algorithms in Investing

According to Mercer's 2024 AI in Investment Management global manager survey, 91% of asset managers either currently use AI (54%) or plan to use it within their investment strategy or asset-class ...

Machine Learning Trends For 2026

ML is poised to become faster and more accessible by 2026. Simply having the support of GenAI already gives it an advantage over other AI-based solutions.
financefeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
science.psu

Foundational Questions in Machine Learning: How to Compare Distributional Data

At its core, machine learning, whether supervised or unsupervised, helps identify patterns in data. In order to make mathematical comparisons among data points, an algorithm often relies on the notion ...
Frontiers

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...
IEEE

Leveraging Machine Learning Algorithms for Robust Credit Card Fraud Detection: A Performance Comparison

Abstract: The implementation of systems designed to detect cyber crimes has become essential for banks and other financial institutions. A variety of approaches have been proposed to combat the ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
Frontiers

Machine learning-based prediction of diabetic peripheral neuropathy: model development and clinical validation

This study analyzed 1,544 diabetic patients from the First Affiliated Hospital of Shandong First Medical University, who were randomly divided into a training cohort (n = 1,082) and a testing cohort ...