Breast Cancer

A Machine-Learning Approach to Identify a Prognostic Cytokine Signature That Is Associated With Nivolumab Clearance in Patients With Advanced Melanoma.

Lower clearance of immune checkpoint inhibitors is a predictor of improved overall survival (OS) in patients with advanced cancer. We investigated a novel approach using machine learning to identify a baseline composite cytokine signature via clearance, which, in turn, could be associated with OS in advanced melanoma. Peripheral nivolumab clearance and cytokine data from patients treated with nivo...

Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).

Breast cancer is one of the leading causes of cancer death among women in worldwide. Early diagnosis of breast cancer improves the chance of survival by aiding proper clinical treatments. The digital mammography examination helps in diagnosing the breast cancer at its earlier stage. In this paper, Multiscale All Convolutional Neural Network (MA-CNN) is developed to assist the radiologist in diagno...

Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Accurately predicting treatment outcome is crucial for creating personalized treatment plans and follow-up schedules. Electronic health records (EHRs)...

Development of a robot-assisted ultrasound-guided radiation therapy (USgRT).

PURPOSE: Radiation treatment is improved by the use of image-guided workflows. This work pursues the approach of using ultrasound (US) as a real-time ...

A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients.

Heterogeneity in intratumoral cancers leads to discrepancies in drug responsiveness, due to diverse genomics profiles. Thus, prediction of drug respon...

Radiomics allows for detection of benign and malignant histopathology in patients with metastatic testicular germ cell tumors prior to post-chemotherapy retroperitoneal lymph node dissection.

OBJECTIVES: To evaluate whether a computed tomography (CT) radiomics-based machine learning classifier can predict histopathology of lymph nodes (LNs)...

Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for t...

Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers.

OBJECTIVE: Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC).

SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso.

At present, with the in-depth study of gene expression data, the significant role of tumor classification in clinical medicine has become more apparen...

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging research, both in diagnostic and therapeutic. For dia...

Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.

Radiogenomics investigates the relationship between imaging phenotypes and genetic expression. Breast cancer is a heterogeneous disease that manifests...

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.

BACKGROUND: Accurate and standardized descriptions of organs at risk (OARs) are essential in radiation therapy for treatment planning and evaluation. ...

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer.

Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation...

Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.

In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR),...

Isolated Hepatic Metastasis of Prostate Cancer with Variable F-fluociclovine Uptake by PET/CT Imaging.

A 74-year-old man presented with rapid rising prostate-specific antigen (PSA) 2 years after treatment of prostate cancer with prostatectomy and salvag...

QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field.

Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous ...

Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduce natural disaster risk. Unfortunately, wetlands a...

Physical and Chemical Stability of Dexamethasone Sodium Phosphate in Intravenous Admixtures Used to Prevent Chemotherapy-Induced Nausea and Vomiting.

Dilute intravenous (IV) admixtures of dexamethasone sodium phosphate (DSP) are becoming increasingly used in antiemetic regimens to prevent chemother...

Multifunctional Nanorobot System for Active Therapeutic Delivery and Synergistic Chemo-photothermal Therapy.

Nanorobots are safe and exhibit powerful functionalities, including delivery, therapy, and diagnosis. Therefore, they are in high demand for the devel...

Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treatment time is critical in stroke diagnosis and trea...