Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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Detection of oral cancer and oral potentially malignant disorders using artificial intelligence-based image analysis.

BACKGROUND: We aimed to construct an artificial intelligence-based model for detecting oral cancer a...

Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art.

Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major ...

Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides.

Cancer diagnosis and management depend upon the extraction of complex information from microscopy im...

Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS)...

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell ...

Automatic text classification of prostate cancer malignancy scores in radiology reports using NLP models.

This paper presents the implementation of two automated text classification systems for prostate can...

A Kernelized Classification Approach for Cancer Recognition Using Markovian Analysis of DNA Structure Patterns as Feature Mining.

Nucleotide-based molecules called DNA and RNA are essential for several biological processes that af...

Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.

BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbi...

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential...

Breaking new ground: can artificial intelligence and machine learning transform papillary glioneuronal tumor diagnosis?

Papillary glioneuronal tumors (PGNTs), classified as Grade I by the WHO in 2016, present diagnostic ...

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study.

BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of W...

New liver window width in detecting hepatocellular carcinoma on dynamic contrast-enhanced computed tomography with deep learning reconstruction.

Changing a window width (WW) alters appearance of noise and contrast of CT images. The aim of this s...

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.

BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), howe...

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poo...

New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.

BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical ...

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients.

BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to...

A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging.

BACKGROUND: Predicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide ...

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