Artificial intelligence in CT and MR imaging for oncological applications

R Paudyal, AD Shah, O Akin, RKG Do, AS Konar… - Cancers, 2023‏ - mdpi.com
Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

B Derraz, G Breda, C Kaempf, F Baenke… - NPJ Precision …, 2024‏ - nature.com
Until recently the application of artificial intelligence (AI) in precision oncology was confined
to activities in drug development and had limited impact on the personalisation of therapy …

Risk management and patient safety in the artificial intelligence era: a systematic review

M Ferrara, G Bertozzi, N Di Fazio, I Aquila, A Di Fazio… - Healthcare, 2024‏ - mdpi.com
Background: Healthcare systems represent complex organizations within which multiple
factors (physical environment, human factor, technological devices, quality of care) …

The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease

MA Zahra, A Al-Taher, M Alquhaidan… - Drug Metabolism and …, 2024‏ - degruyter.com
The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis,
treatment, and prevention of disease Skip to content Should you have institutional access …

[HTML][HTML] Transformers for extracting breast cancer information from Spanish clinical narratives

O Solarte-Pabón, O Montenegro… - Artificial Intelligence in …, 2023‏ - Elsevier
The wide adoption of electronic health records (EHRs) offers immense potential as a source
of support for clinical research. However, previous studies focused on extracting only a …

[HTML][HTML] Advances and challenges in thyroid cancer: The interplay of genetic modulators, targeted therapies, and AI-driven approaches

S Bhattacharya, RK Mahato, S Singh, GK Bhatti… - Life Sciences, 2023‏ - Elsevier
Thyroid cancer continues to exhibit a rising incidence globally, predominantly affecting
women. Despite stable mortality rates, the unique characteristics of thyroid carcinoma …

Artificial Intelligence, Lymphoid Neoplasms, and Prediction of MYC, BCL2, and BCL6 Gene Expression Using a Pan-Cancer Panel in Diffuse Large B-Cell …

J Carreras, N Nakamura - Hemato, 2024‏ - mdpi.com
Background: Artificial intelligence in medicine is a field that is rapidly evolving. Machine
learning and deep learning are used to improve disease identification and diagnosis …

Accurate and fast deep learning dose prediction for a preclinical microbeam radiation therapy study using low-statistics Monte Carlo simulations

F Mentzel, J Paino, M Barnes, M Cameron, S Corde… - Cancers, 2023‏ - mdpi.com
Simple Summary This work describes the development of a fast and accurate machine
learning (ML) 3D U-Net dose engine, trained with Monte Carlo (MC) radiation transport …

Biomedical data analytics for better patient outcomes

A Ghofrani, H Taherdoost - Drug Discovery Today, 2024‏ - Elsevier
Medical professionals today have access to immense amounts of data, which enables them
to make decisions that enhance patient care and treatment efficacy. This innovative strategy …

Empowering the SDM-RDFizer tool for scaling up to complex knowledge graph creation pipelines

E Iglesias, ME Vidal, D Collarana… - Semantic …, 2025‏ - journals.sagepub.com
The significant increase in data volume in recent years has prompted the adoption of
knowledge graphs as valuable data structures for integrating diverse data and metadata …