Oncology/Hematology

Other Cancers

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

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Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral cancer. Very few ...

A Machine Learning-Assisted Nanoparticle-Printed Biochip for Real-Time Single Cancer Cell Analysis.

Cancers are a complex conglomerate of heterogeneous cell populations with varying genotypes and phen...

Machine learning in predicting early remission in patients after surgical treatment of acromegaly: a multicenter study.

PURPOSE: Accurate prediction of postoperative remission is beneficial for effective patient-physicia...

Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.

AIM: To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-...

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

PURPOSE: The main purpose of this study is to construct a system to track the tumor position during ...

Application of ultrasound artificial intelligence in the differential diagnosis between benign and malignant breast lesions of BI-RADS 4A.

BACKGROUND: The classification of Breast Imaging Reporting and Data System 4A (BI-RADS 4A) lesions i...

Optimization of an automated tumor-infiltrating lymphocyte algorithm for improved prognostication in primary melanoma.

Tumor-infiltrating lymphocytes (TIL) have potential prognostic value in melanoma and have been consi...

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning.

OBJECTIVE: Tumour pathology contains rich information, including tissue structure and cell morpholog...

A deep learning nomogram kit for predicting metastatic lymph nodes in rectal cancer.

BACKGROUND: Preoperative diagnoses of metastatic lymph nodes (LNs) by the most advanced deep learnin...

Robust edge-based biomarker discovery improves prediction of breast cancer metastasis.

BACKGROUND: The abundance of molecular profiling of breast cancer tissues entailed active research o...

Preoperative Prediction of Lymph Node Metastasis from Clinical DCE MRI of the Primary Breast Tumor Using a 4D CNN.

In breast cancer, undetected lymph node metastases can spread to distal parts of the body for which ...

Integration of AI and Machine Learning in Radiotherapy QA.

The use of machine learning and other sophisticated models to aid in prediction and decision making ...

Characterizing CDK12-Mutated Prostate Cancers.

PURPOSE: Cyclin-dependent kinase 12 (CDK12) aberrations have been reported as a biomarker of respons...

Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node.

BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) und...

Deep learning radiomics of ultrasonography: Identifying the risk of axillary non-sentinel lymph node involvement in primary breast cancer.

BACKGROUND: Completion axillary lymph node dissection is overtreatment for patients with sentinel ly...

2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma.

For treatment individualisation of patients with locally advanced head and neck squamous cell carcin...

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolesce...

Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients.

Intensity harmonization techniques (IHT) are mandatory to homogenize multicentric MRIs before any qu...

Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics.

Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroi...

Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BACKGROUND: The small number of samples and the curse of dimensionality hamper the better applicatio...

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