Oncology/Hematology

Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review.

BACKGROUND: Pancreatic cancer is the 12th most common cancer worldwide, with an overall survival rate of 4.9%. Early diagnosis of pancreatic cancer is essential for timely treatment and survival. Artificial intelligence (AI) provides advanced models and algorithms for better diagnosis of pancreatic cancer.

Sleep-Energy: An Energy Optimization Method to Sleep Stage Scoring.

Sleep is essential for physical and mental health. Polysomnography (PSG) procedures are labour-intensive and time-consuming, making diagnosing sleep disorders difficult. Automatic sleep staging using Machine Learning (ML) - based methods has been studied extensively, but frequently provides noisier predictions incompatible with typical manually annotated hypnograms. We propose an energy optimizati...

Deep learning of image-derived measures of body composition in pediatric, adolescent, and young adult lymphoma: association with late treatment effects.

OBJECTIVES: The objective of this study was to translate a deep learning (DL) approach for semiautomated analysis of body composition (BC) measures fr...

Deep learning-based detection of patients with bone metastasis from Japanese radiology reports.

PURPOSE: Deep learning (DL) is a state-of-the-art technique for developing artificial intelligence in various domains and it improves the performance ...

[Could robotic surgery really be a revolutionary change in the treatment of kidney cancer in Hungary?].

Robotic-assisted partial nephrectomy (RAPN) was first described in 2004 and, since its introduction in clinical practice, has progressively gained inc...

A Novel Deep-Learning-Based CADx Architecture for Classification of Thyroid Nodules Using Ultrasound Images.

Nodules of thyroid cancer occur in the cells of the thyroid as benign or malign types. Thyroid sonographic images are mostly used for diagnosis of thy...

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

OBJECTIVES: To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features ...

Initial Experience of Robot-Assisted Partial Nephrectomy Using Hinotori Surgical Robot System: Single Institutional Prospective Assessment of Perioperative Outcomes in 30 Cases.

Innovation of robotic surgery is still actively growing, and various novel robotic systems are in the process of development. The objective of this s...

An End-to-End Natural Language Processing System for Automatically Extracting Radiation Therapy Events From Clinical Texts.

PURPOSE: Real-world evidence for radiation therapy (RT) is limited because it is often documented only in the clinical narrative. We developed a natur...

Robot-assisted lateral pelvic lymph node dissection in patients with advanced rectal cancer: a single-center experience of 65 cases.

The treatment of lateral pelvic lymph node (LPLN) metastasis of rectal cancer has evolved because of technical difficulties from open surgery to lapar...

Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

The objective of this study is to develop a radiomic signature constructed from deep learning features and a nomogram for prediction of axillary lymph...

Imaging of Neck Nodes in Head and Neck Cancers - a Comprehensive Update.

Cervical lymph node metastases from head and neck squamous cell cancers significantly reduce disease-free survival and worsen overall prognosis and, h...

Deep learning neural network image analysis of immunohistochemical protein expression reveals a significantly reduced expression of biglycan in breast cancer.

New breast cancer biomarkers have been sought for better tumor characterization and treatment. Among these putative markers, there is Biglycan (BGN). ...

Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.

BACKGROUND: Brain metastasis (BM) is a serious neurological complication of cancer of different origins. The value of deep learning (DL) to identify m...

Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study.

PURPOSE: The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we pres...

Robot-assisted radical nephroureterectomy for upper tract urothelial carcinoma: Peri and postoperative outcomes.

INTRODUCTION: The treatment of urothelial tumours of the upper urinary tract at high risk of specific mortality is based on radical nephroureterectomy...

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function.

The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and softwar...

Probiotic Escherichia coli Nissle 1917 propelled micro-robot with pH sensitivity for hypoxia targeted intestinal tumor therapy.

Poor drug penetration in hypoxia area of solid tumor is a big challenge for intestinal tumor therapy and thus it is crucial to develop an effective st...

Investigation of radiomics and deep convolutional neural networks approaches for glioma grading.

To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader val...

Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images.

Breast cancer is the most common form of cancer and is still the second leading cause of death for women in the world. Early detection and treatment o...