Neoadjuvant therapy for pancreatic cancer

C Springfeld, CR Ferrone, MHG Katz… - Nature Reviews …, 2023 - nature.com
Patients with localized pancreatic ductal adenocarcinoma (PDAC) are best treated with
surgical resection of the primary tumour and systemic chemotherapy, which provides …

Secure, privacy-preserving and federated machine learning in medical imaging

GA Kaissis, MR Makowski, D Rückert… - Nature Machine …, 2020 - nature.com
The broad application of artificial intelligence techniques in medicine is currently hindered
by limited dataset availability for algorithm training and validation, due to the absence of …

Swarm learning for decentralized and confidential clinical machine learning

S Warnat-Herresthal, H Schultze, KL Shastry… - Nature, 2021 - nature.com
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major
goal of precision medicine,. Patients with leukaemia can be identified using machine …

[HTML][HTML] Artificial intelligence in pancreatic cancer

B Huang, H Huang, S Zhang, D Zhang, Q Shi, J Liu… - Theranostics, 2022 - ncbi.nlm.nih.gov
Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%.
The pancreatic cancer patients diagnosed with early screening have a median overall …

[HTML][HTML] Artificial intelligence in gastroenterology: A state-of-the-art review

PT Kröner, MML Engels, BS Glicksberg… - World journal of …, 2021 - ncbi.nlm.nih.gov
The development of artificial intelligence (AI) has increased dramatically in the last 20 years,
with clinical applications progressively being explored for most of the medical specialties …

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

TG Krieger, S Le Blanc, J Jabs, FW Ten… - Nature …, 2021 - nature.com
Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of
cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical'from …

Computational techniques and tools for omics data analysis: state-of-the-art, challenges, and future directions

P Kaur, A Singh, I Chana - Archives of Computational Methods in …, 2021 - Springer
The heterogeneous and high-dimensional nature of omics data presents various challenges
in gaining insights while analysis. In the era of big data, omics data is available as genome …

Pancreas image mining: a systematic review of radiomics

BM Abunahel, B Pontre, H Kumar, MS Petrov - European radiology, 2021 - Springer
Objectives To systematically review published studies on the use of radiomics of the
pancreas. Methods The search was conducted in the MEDLINE database. Human studies …

Development of a novel multiparametric MRI radiomic nomogram for preoperative evaluation of early recurrence in resectable pancreatic cancer

TY Tang, X Li, Q Zhang, CX Guo… - Journal of Magnetic …, 2020 - Wiley Online Library
Background In pancreatic cancer, methods to predict early recurrence (ER) and identify
patients at increased risk of relapse are urgently required. Purpose To develop a radiomic …

Clinical validation of a machine-learning–derived signature predictive of outcomes from first-line oxaliplatin-based chemotherapy in advanced colorectal cancer

JP Abraham, D Magee, C Cremolini, C Antoniotti… - Clinical Cancer …, 2021 - AACR
Abstract Purpose: FOLFOX, FOLFIRI, or FOLFOXIRI chemotherapy with bevacizumab is
considered standard first-line treatment option for patients with metastatic colorectal cancer …