Other Cancers

A review on brain tumor segmentation of MRI images.

The process of segmenting tumor from MRI image of a brain is one of the highly focused areas in the ...

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11.

BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostat...

DRRNet: Dense Residual Refine Networks for Automatic Brain Tumor Segmentation.

Glioma is one of the most common and aggressive brain tumors. Segmentation and subsequent quantitati...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodul...

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment.

Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (H...

A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned.

The successful early diagnosis of brain tumors plays a major role in improving the treatment outcome...

An Intelligent DNA Nanorobot with Enhanced Protein Lysosomal Degradation of HER2.

DNA nanorobots have emerged as new tools for nanomedicine with the potential to ameliorate the deliv...

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptio...

Artificial intelligence and immunotherapy.

MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune...

Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest...

Prediction of local relapse and distant metastasis in patients with definitive chemoradiotherapy-treated cervical cancer by deep learning from [F]-fluorodeoxyglucose positron emission tomography/computed tomography.

BACKGROUND: We designed a deep learning model for assessing F-FDG PET/CT for early prediction of loc...

Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.

PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histologi...

Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine.

In this report, we collected the Raman spectrum of cervical adenocarcinoma and cervical squamous cel...

Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

The question of whether ultrasound point shear wave elastography can differentiate renal cell carcin...

THPep: A machine learning-based approach for predicting tumor homing peptides.

In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specif...

Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study.

Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a method of temporal imaging tha...

Brain tumor detection using statistical and machine learning method.

BACKGROUND AND OBJECTIVE: Brain tumor occurs because of anomalous development of cells. It is one of...

Do no harm: Natural language processing of social media supports safety of aseptic allergen immunotherapy procedures.

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies.

Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-...

NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer.

BACKGROUND: The accurate screening of tumor genomic landscapes for somatic mutations using high-thro...