Data-centric artificial intelligence: A survey

D Zha, ZP Bhat, KH Lai, F Yang, Z Jiang… - ACM Computing …, 2023 - dl.acm.org
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

[PDF][PDF] Artificial intelligence in fraud prevention: Exploring techniques and applications challenges and opportunities

OA Bello, K Olufemi - Computer Science & IT Research Journal, 2024 - researchgate.net
In today's digital age, the proliferation of online transactions, e-commerce, and digital
banking has created new opportunities for fraudsters to exploit vulnerabilities in financial …

Fingpt: Democratizing internet-scale data for financial large language models

XY Liu, G Wang, H Yang, D Zha - arXiv preprint arXiv:2307.10485, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable proficiency in
understanding and generating human-like texts, which may potentially revolutionize the …

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

D Lee, W Chen, L Wang, YC Chan… - Advanced …, 2024 - Wiley Online Library
Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …

Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

RA Abumalloh, M Nilashi, KB Ooi, GWH Tan… - Computers in …, 2024 - Elsevier
Abstract Generative Artificial Intelligence (AI) models serve as powerful tools for
organizations aiming to integrate advanced data analysis and automation into their …

Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer

J Liang, W Zhang, J Yang, M Wu, Q Dai, H Yin… - Nature Machine …, 2023 - nature.com
Tissue biomarkers are crucial for cancer diagnosis, prognosis assessment and treatment
planning. However, there are few known biomarkers that are robust enough to show true …

The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review

D Schwabe, K Becker, M Seyferth, A Klaß… - NPJ Digital …, 2024 - nature.com
The adoption of machine learning (ML) and, more specifically, deep learning (DL)
applications into all major areas of our lives is underway. The development of trustworthy AI …

A survey of multimodal large language model from a data-centric perspective

T Bai, H Liang, B Wan, Y Xu, X Li, S Li, L Yang… - arXiv preprint arXiv …, 2024 - arxiv.org
Multimodal large language models (MLLMs) enhance the capabilities of standard large
language models by integrating and processing data from multiple modalities, including text …

Bigbio: A framework for data-centric biomedical natural language processing

J Fries, L Weber, N Seelam, G Altay… - Advances in …, 2022 - proceedings.neurips.cc
Training and evaluating language models increasingly requires the construction of meta-
datasets--diverse collections of curated data with clear provenance. Natural language …

Implementing machine learning models in business analytics: Challenges, solutions, and impact on decision-making

TV Iyelolu, PO Paul - World Journal of Advanced Research and Reviews, 2024 - wjarr.co.in
This research paper explores the challenges, solutions, and impact of implementing
machine learning (ML) models in business analytics. It delves into the complexities of …