Oncology/Hematology

Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma.

To examine the comparative robustness of computed tomography (CT)-based conventional radiomics and d...

Deep learning-based synthetic dose-weighted LET map generation for intensity modulated proton therapy.

The advantage of proton therapy as compared to photon therapy stems from the Bragg peak effect, whic...

Editorial: World lung cancer awareness month 2022: artificial intelligence for clinical management of lung cancer.

Intersectional analysis of inequalities in self-reported breast cancer screening attendance using supervised machine learning and PROGRESS-Plus framework.

BACKGROUND: Breast cancer is a critical public health concern in Spain, and organized screening prog...

Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography.

Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including dec...

Robot-Assisted Pelvic Dissection for Enlarged Lymph Nodes in Melanoma Improves Recovery with Equivalent Oncological Outcomes to Open Pelvic Dissection.

BACKGROUND: Robot-assisted pelvic lymph node dissection (rPLND) has been reported in heterogenous gr...

A deep learning model based on MRI for prediction of vessels encapsulating tumour clusters and prognosis in hepatocellular carcinoma.

PURPOSE: This study aimed to build and evaluate a deep learning (DL) model to predict vessels encaps...

Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes.

OBJECTIVE: Deep learning has been shown to be useful in detecting breast cancer metastases by analyz...

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was t...

A computed tomography urography-based machine learning model for predicting preoperative pathological grade of upper urinary tract urothelial carcinoma.

OBJECTIVES: Development and validation of a computed tomography urography (CTU)-based machine learni...

Towards Real-Time Sleep Stage Prediction and Online Calibration Based on Architecturally Switchable Deep Learning Models.

Despite the recent advances in automatic sleep staging, few studies have focused on real-time sleep ...

Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable ...

Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology.

INTRODUCTION: Artificial intelligence (AI)-based technologies embody countless solutions in radiatio...

Implementing a deep learning model for automatic tongue tumour segmentation in ex-vivo 3-dimensional ultrasound volumes.

Three-dimensional (3D) ultrasound can assess the margins of resected tongue carcinoma during surgery...

Deep-Learning-Based Nanomechanical Vibration for Rapid and Label-Free Assay of Epithelial Mesenchymal Transition.

Cancer is a profound danger to our life and health. The classification and related studies of epithe...

Artificial intelligence in the detection of skin cancer: State of the art.

The incidence of melanoma is increasing rapidly. This cancer has a good prognosis if detected early....

Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.

BACKGROUND: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the...

(mistletoe) extract for dogs with cancer?

Compared with the options available to human patients with cancer, treatment choices for dogs are of...

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, ...

Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support-a reader study.

OBJECTIVES: The aim of our study was to examine how breast radiologists would be affected by high ca...

A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

BACKGROUND: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) ...