A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
Radiomics in precision medicine for gastric cancer: opportunities and challenges
Q Chen, L Zhang, S Liu, J You, L Chen, Z **… - European …, 2022 - Springer
Objectives Radiomic features derived from routine medical images show great potential for
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …
Prognostic and predictive value of a pathomics signature in gastric cancer
D Chen, M Fu, L Chi, L Lin, J Cheng, W Xue… - Nature …, 2022 - nature.com
The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate
information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer …
information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer …
Long-term cancer survival prediction using multimodal deep learning
The age of precision medicine demands powerful computational techniques to handle high-
dimensional patient data. We present MultiSurv, a multimodal deep learning method for long …
dimensional patient data. We present MultiSurv, a multimodal deep learning method for long …
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study
Background Peritoneal recurrence is the predominant pattern of relapse after curative-intent
surgery for gastric cancer and portends a dismal prognosis. Accurate individualised …
surgery for gastric cancer and portends a dismal prognosis. Accurate individualised …
A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study
Background Induction chemotherapy (ICT) plus concurrent chemoradiotherapy (CCRT) and
CCRT alone were the optional treatment regimens in locoregionally advanced …
CCRT alone were the optional treatment regimens in locoregionally advanced …
Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology
Z Wang, Y Liu, X Niu - Seminars in Cancer Biology, 2023 - Elsevier
Gastric cancer is a leading contributor to cancer incidence and mortality globally. Recently,
artificial intelligence approaches, particularly machine learning and deep learning, are …
artificial intelligence approaches, particularly machine learning and deep learning, are …
Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer
Background and purpose Delineation of organs at risk (OARs), such as the bladder, rectum
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …
Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study
Background and Aims Narrow-band imaging with magnifying endoscopy (ME-NBI) has
shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in …
shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in …
Effectiveness of artificial intelligence for personalized medicine in neoplasms: a systematic review
Purpose. Artificial intelligence (AI) techniques are used in precision medicine to explore
novel genotypes and phenotypes data. The main aims of precision medicine include early …
novel genotypes and phenotypes data. The main aims of precision medicine include early …