Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Potential and limitations of radiomics in neuro-oncology.

Radiomics seeks to apply classical methods of image processing to obtain quantitative parameters fro...

Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.

Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from ben...

Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

BACKGROUND: In recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to...

Evaluating machine learning methodologies for identification of cancer driver genes.

Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer d...

Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears.

Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diag...

A different overview of staging PET/CT images in patients with esophageal cancer: the role of textural analysis with machine learning methods.

OBJECTIVE: This study evaluates the ability of several machine learning (ML) algorithms, developed u...

Oncological, Surgical and Functional Outcomes of Transoral Robotic Cordectomy for Early Glottic Carcinoma.

OBJECTIVE: To investigate oncological, surgical and functional outcomes of transoral robotic surgery...

Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non-muscle-invasive Bladder Cancer.

Despite being standard tools for decision-making, the European Organisation for Research and Treatme...

Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer.

Machine learning (ML) holds great promise for impacting healthcare delivery; however, to date most m...

MRI Based Radiomics Approach With Deep Learning for Prediction of Vessel Invasion in Early-Stage Cervical Cancer.

This article aims to build deep learning-based radiomic methods in differentiating vessel invasion f...

Knowledge-Powered Deep Breast Tumor Classification With Multiple Medical Reports.

Breast tumor classification with multiple medical reports such as B-ultrasound, Mammography (X-ray) ...

Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors.

Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths wor...

A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.

INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assi...

Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma.

Deep learning has emerged as the technique of choice for identifying hidden patterns in cell imaging...

Domain adaptation for segmentation of critical structures for prostate cancer therapy.

Preoperative assessment of the proximity of critical structures to the tumors is crucial in avoiding...

An assessment of contamination pickup on ground robotic vehicles for nuclear surveying application.

Ground robotic vehicles are often deployed to inspect areas where radioactive floor contamination is...

The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clini...

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate bi...

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