activity
19972023
most citedArtificial Neural Networks for Solving Ordinary and Partial Differential Equations

2.4k citations · 2.7k across the 7 of their papers we have counts for

collaborators

7 papers

cs.CY2023★ 39 cited

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…

cs.HC2022★ 4 cited

Smart Insole: A Gait Analysis Monitoring Platform Targeting Parkinson Disease Patients Based on Insoles

Dimitrios Boucharas, Christos Androutsos, George Gkois +11

During the preceding decades, human gait analysis has been the center of attention for the scientific community, while the association between gait analysis and overall health moni…

eess.IV2021

A new smart-cropping pipeline for prostate segmentation using deep learning networks

Dimitrios G. Zaridis, Eugenia Mylona, Nikolaos S. Tachos +4

Prostate segmentation from magnetic resonance imaging (MRI) is a challenging task. In recent years, several network architectures have been proposed to automate this process and al…

eess.IV2019★ 48 cited

3D Reconstruction of Coronary Arteries and Atherosclerotic Plaques based on Computed Tomography Angiography Images

Vassiliki I. Kigka, George Rigas, Antonis Sakellarios +10

The purpose of this study is to present a new semi-automated methodology for three-dimensional (3D) reconstruction of coronary arteries and their plaque morphology using Computed T…

physics.med-ph2016

3-D Registration on Carotid Artery imaging data: MRI for different timesteps

Paschalis A. Bizopoulos, Antonis Sakellarios, Lampros K. Michalis +2

A common problem which is faced by the researchers when dealing with arterial carotid imaging data is the registration of the geometrical structures between different imaging modal…

physics.comp-ph1997★ 2.4k cited

Artificial Neural Networks for Solving Ordinary and Partial Differential Equations

I. E. Lagaris, A. Likas, D. I. Fotiadis

We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. T…

quant-ph1997★ 167 cited

Artificial Neural Network Methods in Quantum Mechanics

I. E. Lagaris, A. Likas, D. I. Fotiadis

In a previous article we have shown how one can employ Artificial Neural Networks (ANNs) in order to solve non-homogeneous ordinary and partial differential equations. In the prese…