Oncology/Hematology

Breast Cancer

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Showing 1009-1029 of 6,469 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...

Coupling of Trastuzumab chromatographic profiling with machine learning tools: A complementary approach for biosimilarity and stability assessment.

Biosimilar products present a growing opportunity to improve the global healthcare systems. The amou...

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 ...

Introducing artificial intelligence to the radiation early warning system.

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

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...

Radiation Oncologists' Perceptions of Adopting an Artificial Intelligence-Assisted Contouring Technology: Model Development and Questionnaire Study.

BACKGROUND: An artificial intelligence (AI)-assisted contouring system benefits radiation oncologist...

5FU-loaded PCL/Chitosan/FeO Core-Shell Nanofibers Structure: An Approach to Multi-Mode Anticancer System.

5-Fluorouracil (5FU) and FeO nanoparticles were encapsulated in core-shell polycaprolactone (PCL)/c...

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence...

Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

The achievement of the pathologic complete response (pCR) has been considered a metric for the succe...

Deep Learning-Based CT Imaging in Diagnosing Myeloma and Its Prognosis Evaluation.

Imaging examination plays an important role in the early diagnosis of myeloma. The study focused on ...

Deep Learning: a Promising Method for Histological Class Prediction of Breast Tumors in Mammography.

The objective of the study was to determine if the pathology depicted on a mammogram is either benig...

Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce.

OBJECTIVE: Radiation oncology is a continually evolving speciality. With the development of new imag...

DeepWL: Robust EPID based Winston-Lutz analysis using deep learning, synthetic image generation and optical path-tracing.

Radiation therapy requires clinical linear accelerators to be mechanically and dosimetrically calibr...

Chemotherapeutic potential of Cayratia trifolia L nhexane extract on A2780 cells.

It is of interest to report the chemotherapeutic (drug target based) potential of n-hexane Cayratia ...

Artificial intelligence: The opinions of radiographers and radiation therapists in Ireland.

INTRODUCTION: Implementation of Artificial Intelligence (AI) into medical imaging is much debated. D...

A deep learning-based dual-omics prediction model for radiation pneumonitis.

PURPOSE: Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This st...

Artificial Intelligence in Radiation Therapy.

Artificial intelligence (AI) has great potential to transform the clinical workflow of radiotherapy....

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