Other Cancers

Robotic Actuation-Mediated Quantitative Mechanogenetics for Noninvasive and On-Demand Cancer Therapy.

Cell mechanotransduction signals are important targets for physical therapy. However, current physio...

Application of deep learning in radiation therapy for cancer.

In recent years, with the development of artificial intelligence, deep learning has been gradually a...

Malignancy diagnosis of liver lesion in contrast enhanced ultrasound using an end-to-end method based on deep learning.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is considered as an efficient tool for focal liver l...

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEU...

Deep learning-based target decomposition for markerless lung tumor tracking in radiotherapy.

BACKGROUND: In radiotherapy, real-time tumor tracking can verify tumor position during beam delivery...

Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma.

BACKGROUND: Surgery combined with radiotherapy substantially escalates the likelihood of encounterin...

The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study.

Accurately predicting the prognosis of Gastrointestinal stromal tumor (GIST) patients is an importan...

Investigation of deep learning model for predicting immune checkpoint inhibitor treatment efficacy on contrast-enhanced computed tomography images of hepatocellular carcinoma.

Although the use of immune checkpoint inhibitors (ICIs)-targeted agents for unresectable hepatocellu...

Mortality risk prediction for primary appendiceal cancer.

BACKGROUND: Accurately predicting survival in patients with cancer is crucial for both clinical deci...

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model usi...

Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate...

Use of Machine Learning to Optimize Referral for Early Palliative Care: Are Prognostic Predictions Enough?

High-dose-rate Brachytherapy Monotherapy in Patients With Localised Prostate Cancer: Dose Modelling and Optimisation Using Computer Algorithms.

AIMS: Interstitial high-dose-rate brachytherapy (HDR-BT) is an effective therapy modality for patien...

A deep learning method for multi-task intelligent detection of oral cancer based on optical fiber Raman spectroscopy.

In the fight against oral cancer, innovative methods like Raman spectroscopy and deep learning have ...

RETRACTED: Refining molecular subtypes and risk stratification of ovarian cancer through multi-omics consensus portfolio and machine learning.

Ovarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classificatio...

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising ...

A systematic review of machine learning-based tumor-infiltrating lymphocytes analysis in colorectal cancer: Overview of techniques, performance metrics, and clinical outcomes.

The incidence of colorectal cancer (CRC), one of the deadliest cancers around the world, is increasi...

Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a l...

Fully Automated Identification of Lymph Node Metastases and Lymphovascular Invasion in Endometrial Cancer From Multi-Parametric MRI by Deep Learning.

BACKGROUND: Early and accurate identification of lymphatic node metastasis (LNM) and lymphatic vascu...

Automatic segmentation of hepatocellular carcinoma on dynamic contrast-enhanced MRI based on deep learning.

. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies...

An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI.

Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic ...