Oncology/Hematology

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

15,652 articles
Stay Ahead - Weekly Oncology/Hematology research updates
Subscribe
Browse Categories
Showing 6385-6405 of 15,652 articles
The stability of oncologic MRI radiomic features and the potential role of deep learning: a review.

The use of MRI radiomic models for the diagnosis, prognosis and treatment response prediction of tum...

The future of early cancer detection.

A proactive approach to detecting cancer at an early stage can make treatments more effective, with ...

Robot-Assisted Radical Prostatectomy for Potential Cancer Control in Patients with Metastatic Prostate Cancer.

Recently, cytoreductive prostatectomy for metastatic prostate cancer (mPCa) has been associated with...

Improved Artificial Neural Network with State Order Dataset Estimation for Brain Cancer Cell Diagnosis.

Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient diag...

Robotic CME in obese patients: advantage of robotic ultrasound scan for vascular dissection.

Complete mesocolic excision (CME) in right-sided colon cancers appears to confer oncological benefit...

Tc-PSMA targeted robot-assisted radioguided surgery during radical prostatectomy and extended lymph node dissection of prostate cancer patients.

OBJECTIVE: The feasibility of tracer production of technetium (Tc)-prostate-specific membrane antige...

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging.

This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cel...

Deep learning model for tongue cancer diagnosis using endoscopic images.

In this study, we developed a deep learning model to identify patients with tongue cancer based on a...

A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system.

Automated classification and detection of brain abnormalities like a tumor(s) in reconstructed micro...

MBP-11901 Inhibits Tumor Growth of Hepatocellular Carcinoma through Multitargeted Inhibition of Receptor Tyrosine Kinases.

Hepatocellular carcinomas (HCCs) are aggressive tumors with a poor prognosis. Approved first-line tr...

Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.

BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images a...

Artificial intelligence in prostate cancer: Definitions, current research, and future directions.

Multiple novel modalities tasking artificial intelligence based computational pathology applications...

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development a...

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.

Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed...

3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility.

This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory ...

Deep learning-based algorithm improved radiologists' performance in bone metastases detection on CT.

OBJECTIVES: To develop and evaluate a deep learning-based algorithm (DLA) for automatic detection of...

Assessment of deep learning assistance for the pathological diagnosis of gastric cancer.

Previous studies on deep learning (DL) applications in pathology have focused on pathologist-versus-...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic ...

Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics.

Our aim is to define the capabilities of radiomics and machine learning in predicting pseudoprogress...

Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review.

BACKGROUND: Describe and evaluate the methodological conduct of prognostic prediction models develop...

Browse Categories