Original Research

Published on 22 Mar 2024

Enhancing cancer stage prediction through hybrid deep neural networks: a comparative study

in Machine Learning and Artificial Intelligence

Alina Amanzholova
Aysun Coşkun

Frontiers in Big Data

doi 10.3389/fdata.2024.1359703

1,957 views
1 citation

Original Research

Published on 08 Jan 2024

A novel approach to fake news classification using LSTM-based deep learning models

in Machine Learning and Artificial Intelligence

Halyna Padalko
Vasyl Chomko
Dmytro Chumachenko

Frontiers in Big Data

doi 10.3389/fdata.2023.1320800

4,425 views
6 citations

Original Research

Published on 14 Nov 2023

Integrating geometries of ReLU feedforward neural networks

in Machine Learning and Artificial Intelligence

Yajing Liu
Turgay Caglar
Christopher Peterson
Michael Kirby

Frontiers in Big Data

doi 10.3389/fdata.2023.1274831

1,255 views

Mini Review

Published on 23 Aug 2023

Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer

in Machine Learning and Artificial Intelligence

Casey Watters
Michal K. Lemanski

Frontiers in Big Data

doi 10.3389/fdata.2023.1224976

10,477 views
17 citations

Review

Published on 17 Aug 2023

Discovering anomalies in big data: a review focused on the application of metaheuristics and machine learning techniques

in Machine Learning and Artificial Intelligence

Claudia Cavallaro
Vincenzo Cutello
Mario Pavone
Francesco Zito

Frontiers in Big Data

doi 10.3389/fdata.2023.1179625

3,376 views
3 citations

Perspective

Published on 07 Aug 2023

Artificial intelligence research strategy of the United States: critical assessment and policy recommendations

in Machine Learning and Artificial Intelligence

Furkan Gursoy
Ioannis A. Kakadiaris

Frontiers in Big Data

doi 10.3389/fdata.2023.1206139

3,243 views

Original Research

Published on 04 Aug 2023

Arrival times by Recurrent Neural Network for induced seismic events from a permanent network

in Machine Learning and Artificial Intelligence

Petr Kolar
Umair bin Waheed
Leo Eisner
Petr Matousek

Frontiers in Big Data

doi 10.3389/fdata.2023.1174478

1,676 views

Methods

Published on 24 Jul 2023

Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning

in Machine Learning and Artificial Intelligence

Revathy Venkataramanan
Swati Padhee
Saini Rohan Rao
Ronak Kaoshik
Anirudh Sundara Rajan
Amit Sheth

Frontiers in Big Data

doi 10.3389/fdata.2023.1200840

1,720 views

Original Research

Published on 20 Jul 2023

Too much information is no information: how machine learning and feature selection could help in understanding the motor control of pointing

in Machine Learning and Artificial Intelligence

Elizabeth Thomas
Ferid Ben Ali
Arvind Tolambiya
Florian Chambellant
Jérémie Gaveau

Frontiers in Big Data

doi 10.3389/fdata.2023.921355

2,036 views
4 citations

Original Research

Published on 15 Jun 2023

PME: pruning-based multi-size embedding for recommender systems

in Machine Learning and Artificial Intelligence

Zirui Liu
Qingquan Song
Li Li
Soo-Hyun Choi
Rui Chen
Xia Hu

Frontiers in Big Data

doi 10.3389/fdata.2023.1195742

2,106 views

Original Research

Published on 09 Jun 2023

Ensemble-based classification approach for PM2.5 concentration forecasting using meteorological data

in Machine Learning and Artificial Intelligence

S. Saminathan
C. Malathy

Frontiers in Big Data

doi 10.3389/fdata.2023.1175259

2,551 views
3 citations

Conceptual Analysis

Published on 12 May 2023

Just preparation for war and AI-enabled weapons

in Machine Learning and Artificial Intelligence

Mitt Regan
Jovana Davidovic

Frontiers in Big Data

doi 10.3389/fdata.2023.1020107

4,184 views
1 citation

Original Research

Published on 30 Mar 2023

Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals

in Machine Learning and Artificial Intelligence

Pavel Latyshev
Fedor Pavlov
Alan Herbert
Maria Poptsova

Frontiers in Big Data

doi 10.3389/fdata.2023.1140663

2,906 views

Original Research

Published on 24 Mar 2023

A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity

in Machine Learning and Artificial Intelligence

Marko Tumbas
Sofija Markovic
Igor Salom
Marko Djordjevic

Frontiers in Big Data

doi 10.3389/fdata.2023.1038283

2,125 views
4 citations

Original Research

Published on 21 Feb 2023

Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering

in Machine Learning and Artificial Intelligence

Yu Zhu
Santiago Segarra

Frontiers in Big Data

doi 10.3389/fdata.2023.1020173

1,751 views
2 citations

Original Research

Published on 25 Jan 2023

Predicting the distribution of COVID-19 through CGAN—Taking Macau as an example

in Machine Learning and Artificial Intelligence

Liang Zheng
Yile Chen
Shan Jiang
Junxin Song
Jianyi Zheng

Frontiers in Big Data

doi 10.3389/fdata.2023.1008292

2,757 views
1 citation

Navigation group

Articles

Enhancing cancer stage prediction through hybrid deep neural networks: a comparative study

A novel approach to fake news classification using LSTM-based deep learning models

Integrating geometries of ReLU feedforward neural networks

Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer

Discovering anomalies in big data: a review focused on the application of metaheuristics and machine learning techniques

Artificial intelligence research strategy of the United States: critical assessment and policy recommendations

Arrival times by Recurrent Neural Network for induced seismic events from a permanent network

Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning

Too much information is no information: how machine learning and feature selection could help in understanding the motor control of pointing

PME: pruning-based multi-size embedding for recommender systems

Ensemble-based classification approach for PM2.5 concentration forecasting using meteorological data

Just preparation for war and AI-enabled weapons

Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals

A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity

Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering

Predicting the distribution of COVID-19 through CGAN—Taking Macau as an example