Advancing Neurological Disease Prediction through Machine Learning Techniques

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...

Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
GitHub

Remaining Useful Life (RUL) prediction of rolling element bearings using vibration signal analysis, feature engineering, FFT-based features, and machine learning models (Random ...

This project predicts the Remaining Useful Life (RUL) of industrial bearings using vibration signal analysis and machine learning. Unlike common bearing fault detection projects that use artificially ...
The Lancet

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

aDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA bDepartment of Medicine, University of California Los Angeles, Los Angeles, CA, USA cDepartment of Medicine, ...
IEEE

Online Reinforcement Learning Algorithm Design for Adaptive Optimal Consensus Control Under Interval Excitation

Abstract: This article proposes online data-based reinforcement learning (RL) algorithm for adaptive output consensus control of heterogeneous multiagent systems (MASs) with unknown dynamics. First, ...
IEEE

IntML-KNN: A Few-Shot Radio Frequency Fingerprint Identification Scheme for LoRa Devices

Abstract: Deep learning (DL) is widely used in radio frequency fingerprint identification (RFFI). However, in few-shot case, traditional DL-based RFFI need to construct auxiliary dataset to realize ...