Oncology/Hematology

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

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An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy.

Prostate cancer is a leading cause of morbidity and mortality for adult males in the US. The diagnos...

Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.

PURPOSE: Nasopharyngeal carcinoma (NPC) is a category of tumors with high incidence in head-and-neck...

Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly i...

Development and evaluation of a deep neural network for histologic classification of renal cell carcinoma on biopsy and surgical resection slides.

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classifica...

Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study.

BACKGROUND: Targeted therapy and immunotherapy put forward higher demands for accurate lung cancer c...

IL-8, MSPa, MIF, FGF-9, ANG-2 and AgRP collection were identified for the diagnosis of colorectal cancer based on the support vector machine model.

Colorectal cancer (CRC) is one of the most common cancer, and the early detection of CRC is essentia...

A comparison of surgical outcomes among robotic cases performed with an employed surgical assist versus a second surgeon as the assist.

To examine whether utilizing an employed surgical first assistant or a physician as an assistant dur...

Reperfusion Therapy in Acute Ischemic Stroke with Active Cancer: A Meta-Analysis Aided by Machine Learning.

OBJECTIVES: While the prevalence of active cancer patients experiencing acute stroke is increasing, ...

Collaborative Robotic Assistant Platform for Endonasal Surgery: Preliminary In-Vitro Trials.

Endonasal surgery is a minimally invasive approach for the removal of pituitary tumors (sarcomas). I...

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently,...

Current applications of deep-learning in neuro-oncological MRI.

PURPOSE: Magnetic Resonance Imaging (MRI) provides an essential contribution in the screening, detec...

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accuratel...

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative me...

Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer.

BACKGROUND: Survival and drug response are two highly emphasized clinical outcomes in cancer researc...

Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Background Conventional radiologic modalities perform poorly in the radiated rectum and are often un...

AAPM Task Group 264: The safe clinical implementation of MLC tracking in radiotherapy.

The era of real-time radiotherapy is upon us. Robotic and gimbaled linac tracking are clinically est...

A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a particularly aggressive tumor subtype, and dihydroorotate dehydro...

Automated evaluation of tumor spheroid behavior in 3D culture using deep learning-based recognition.

Three-dimensional in vitro tumor models provide more physiologically relevant responses to drugs tha...

MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers.

Brain tumor classification plays an important role in clinical diagnosis and effective treatment. In...

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer.

This study addresses the core issue facing a surgical team during breast cancer surgery: quantitativ...

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