Oncology/Hematology

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

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Showing 6910-6930 of 15,647 articles
Comparative optimization of global solar radiation forecasting using machine learning and time series models.

The increasing use of solar energy as a source of renewable energy has led to increasing the interes...

Stem-cell based, machine learning approach for optimizing natural killer cell-based personalized immunotherapy for high-grade ovarian cancer.

Advanced high-grade serous ovarian cancer continues to be a therapeutic challenge for those affected...

Prediction of Essential Genes in Comparison States Using Machine Learning.

Identifying essential genes in comparison states (EGS) is vital to understanding cell differentiatio...

MISSIM: An Incremental Learning-Based Model With Applications to the Prediction of miRNA-Disease Association.

In the past few years, the prediction models have shown remarkable performance in most biological co...

Few-Shot Breast Cancer Metastases Classification via Unsupervised Cell Ranking.

Tumor metastases detection is of great importance for the treatment of breast cancer patients. Vario...

Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art.

Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technol...

The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study.

BACKGROUND: The prediction of survival is valuable to optimize treatment of metastatic long-bone dis...

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breas...

Natural language processing and machine learning to assist radiation oncology incident learning.

PURPOSE: To develop a Natural Language Processing (NLP) and Machine Learning (ML) pipeline that can ...

A Cascade Flexible Neural Forest Model for Cancer Subtypes Classification on Gene Expression Data.

The correct classification of cancer subtypes is of great significance for the in-depth study of can...

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular car...

Introducing artificial intelligence to the radiation early warning system.

Although radiation level is a serious concern which requires continuous monitoring, many existing sy...

Rapidly Fatal Ectopic Adrenocorticotropic Hormone Syndrome in a 9-Year-Old Girl With Ewing Sarcoma.

BACKGROUND: Ewing sarcoma (ES) with ectopic adrenocorticotropic hormone (ACTH) syndrome (ectopic ACT...

A Pyramid Architecture-Based Deep Learning Framework for Breast Cancer Detection.

Breast cancer diagnosis is a critical step in clinical decision making, and this is achieved by maki...

Deep Learning-based Reconstruction for Lower-Dose Pediatric CT: Technical Principles, Image Characteristics, and Clinical Implementations.

Optimizing the CT acquisition parameters to obtain diagnostic image quality at the lowest possible r...

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse e...

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images.

The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy opt...

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