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Artificial intelligence for prediction of treatment outcomes in breast cancer: Systematic review of design, reporting standards, and bias
Background Artificial intelligence (AI) has the potential to personalize treatment strategies for
patients with cancer. However, current methodological weaknesses could limit clinical …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
available for analysis. However, in traditional data analysis systems, data need to be moved …