Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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X-ray dose profiles using artificial neural networks.

This paper introduces a novel computational method to simulate and predict radiation dose profiles i...

Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional ...

Deep Learning Prediction of Pathologic Complete Response in Breast Cancer Using MRI and Other Clinical Data: A Systematic Review.

Breast cancer patients who have pathological complete response (pCR) to neoadjuvant chemotherapy (NA...

Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images.

The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). T...

Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks.

Developments in artificial intelligence, particularly convolutional neural networks and deep learnin...

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey.

Reinforcement learning takes sequential decision-making approaches by learning the policy through tr...

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug ...

Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.

BACKGROUND: Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerato...

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models.

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation th...

Emergence of MXene and MXene-Polymer Hybrid Membranes as Future- Environmental Remediation Strategies.

The continuous deterioration of the environment due to extensive industrialization and urbanization ...

Prediction of chemotherapy-related complications in pediatric oncology patients: artificial intelligence and machine learning implementations.

Although the overall incidence of pediatric oncological diseases tends to increase over the years, i...

Fast Deformable Image Registration for Real-Time Target Tracking During Radiation Therapy Using Cine MRI and Deep Learning.

PURPOSE: We developed a deep learning (DL) model for fast deformable image registration using 2-dime...

D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images.

Stem cell-derived organoids are a promising tool to model native human tissues as they resemble huma...

Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatmen...

Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

For accurate respiration gated radiation therapy, compensation for the beam latency of the beam cont...

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