Oncology/Hematology

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

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Integration of transcriptomics and machine learning for insights into breast cancer: exploring lipid metabolism and immune interactions.

BACKGROUND: Breast cancer (BRCA) represents a substantial global health challenge marked by inadequa...

Machine learning-based new classification for immune infiltration of gliomas.

BACKGROUND: Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited ef...

Patient-Specific Deep Learning Tracking Framework for Real-Time 2D Target Localization in Magnetic Resonance Imaging-Guided Radiation Therapy.

PURPOSE: We propose a tumor tracking framework for 2D cine magnetic resonance imaging (MRI) based on...

An optimized siamese neural network with deep linear graph attention model for gynaecological abdominal pelvic masses classification.

An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovari...

Aggressiveness classification of clear cell renal cell carcinoma using registration-independent radiology-pathology correlation learning.

BACKGROUND: Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Clear ce...

Robust brain MRI image classification with SIBOW-SVM.

Primary Central Nervous System tumors in the brain are among the most aggressive diseases affecting ...

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study.

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, a...

Predicting Breast Cancer Relapse from Histopathological Images with Ensemble Machine Learning Models.

Relapse and metastasis occur in 30-40% of breast cancer patients, even after targeted treatments lik...

Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials.

This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinic...

Deep Learning Segmentation of Chromogenic Dye RNAscope From Breast Cancer Tissue.

RNAscope staining of breast cancer tissue allows pathologists to deduce genetic characteristics of t...

Lightweight skin cancer detection IP hardware implementation using cycle expansion and optimal computation arrays methods.

Skin cancer is recognized as one of the most perilous diseases globally. In the field of medical ima...

The SINFONIA project repository for AI-based algorithms and health data.

The SINFONIA project's main objective is to develop novel methodologies and tools that will provide ...

Addressing Challenges in Skin Cancer Diagnosis: A Convolutional Swin Transformer Approach.

Skin cancer is one of the top three hazardous cancer types, and it is caused by the abnormal prolife...

Multiparametric MRI-Based Deep Learning Models for Preoperative Prediction of Tumor Deposits in Rectal Cancer and Prognostic Outcome.

RATIONALE AND OBJECTIVES: To investigate the predictive value of a deep learning model based on mult...

Bloodstream Infections in Childhood Acute Myeloid Leukemia and Machine Learning Models: A Single-institutional Analysis.

Childhood acute myeloid leukemia (AML) requires intensive chemotherapy, which may result in life-thr...

Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies a...

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