Artificial intelligence for prediction of treatment outcomes in breast cancer: Systematic review of design, reporting standards, and bias

C Corti, M Cobanaj, F Marian, EC Dee, MR Lloyd… - Cancer Treatment …, 2022‏ - Elsevier
Background Artificial intelligence (AI) has the potential to personalize treatment strategies for
patients with cancer. However, current methodological weaknesses could limit clinical …

Perfect match: radiomics and artificial intelligence in cardiac imaging

B Baeßler, S Engelhardt, A Hekalo… - Circulation …, 2024‏ - ahajournals.org
Cardiovascular diseases remain a significant health burden, with imaging modalities like
echocardiography, cardiac computed tomography, and cardiac magnetic resonance …

[HTML][HTML] Trustworthy AI: Securing sensitive data in large language models

G Feretzakis, VS Verykios - AI, 2024‏ - mdpi.com
Large language models (LLMs) have transformed Natural Language Processing (NLP) by
enabling robust text generation and understanding. However, their deployment in sensitive …

Current state of implementation of in silico tools in the biopharmaceutical industry—Proceedings of the 5th modeling workshop

F Wittkopp, J Welsh, R Todd, A Staby… - Biotechnology and …, 2024‏ - Wiley Online Library
The fifth modeling workshop (5MW) was held in June 2023 at Favrholm, Denmark and
sponsored by Recovery of Biological Products Conference Series. The goal of the workshop …

Distributed learning in healthcare

A Tuladhar, D Rajashekar, ND Forkert - … intelligence and big data for E …, 2023‏ - Springer
Artificial intelligence and machine learning models are key tools in advancing data-driven
healthcare solutions that aim to improve patient care and outcomes. A key step in …

Tools for Healthcare Data Lake Infrastructure Benchmarking

T Dolci, L Amata, C Manco, F Azzalini… - Information Systems …, 2024‏ - Springer
Vast amounts of medical data are generated every day, and constitute a crucial asset to
improve therapy outcomes, medical treatments and healthcare costs. Data lakes are a …

Simulafed: an enhanced federated simulated environment for privacy and security in health

JM Rivas, C Fernandez-Basso, R Morcillo-Jimenez… - Computing, 2025‏ - Springer
Federated learning enables collaborative data analysis without the need to share sensitive
information among participants, addressing privacy concerns in domains such as healthcare …

Integration of heterogeneous biological data in multiscale mechanistic model calibration: application to lung adenocarcinoma

JL Palgen, A Perrillat-Mercerot, N Ceres, E Peyronnet… - Acta biotheoretica, 2022‏ - Springer
Mechanistic models are built using knowledge as the primary information source, with well-
established biological and physical laws determining the causal relationships within the …

Introduction and comparison of novel decentral learning schemes with multiple data pools for privacy-preserving ECG classification

M Baumgartner, SPK Veeranki, D Hayn… - Journal of healthcare …, 2023‏ - Springer
Artificial intelligence and machine learning have led to prominent and spectacular
innovations in various scenarios. Application in medicine, however, can be challenging due …

Personal health train architecture with dynamic cloud staging

LO Bonino da Silva Santos, L Ferreira Pires… - SN computer …, 2022‏ - Springer
Scientific advances, especially in the healthcare domain, can be accelerated by making data
available for analysis. However, in traditional data analysis systems, data need to be moved …