Frontiers

PMJDM: a multi-task joint detection model for plant disease identification

Shandong Province University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang, China Introduction: Plant disease detection is critical for ensuring ...
IEEE

Parkinson's Disease Detection Using Deep Learning

Abstract: Parkinsin's disease (PD) is very important to make early diagnoses of such neurodegenerative disorders leading to progressive motor and non-motor symptoms. Traditional methods of diagnosis ...
IEEE

Analysis of Freezing of Gait in Parkinson’s Disease Detection Using a Multimodal Prototype Learning Framework

Abstract: Patients with severe Parkinson’s disease (PD) frequently have freezing of gait (FOG), a gait disability. By anticipating FOG before it occurs, pre-emptive cueing can either prevent FOG or ...
Cancer Research

Detection of Cancers Three Years prior to Diagnosis Using Plasma Cell-Free DNA

1Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland. 2The Ludwig Center for Cancer Genetics and Therapeutics, Baltimore, Maryland. 3The Sol ...
GitHub

Self-Learning-VAE-for-EEG-Artifact-Removal

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
Frontiers

An explainable digital twin framework for skin cancer analysis using early activation meta-learner

Skin cancer is among the most common cancers globally, which calls for timely and precise diagnosis for successful therapy. Conventional methods of diagnosis, including dermoscopy and histopathology, ...