Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Breast cancer is the most prevalent malignancy in the US and the third highest cause of cancer-related mortality worldwide. Regular mammography screening has been attributed with doubling the rate of early cancer detection over the past three decades, yet estimates of mammographic accuracy in the hands of experienced radiologists remain suboptimal with sensitivity ranging from 62 to 87% and specif...
With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features ...
Human Flap endonuclease1 (FEN1) is an enzyme that is indispensable for DNA replication and repair processes and inhibition of its Flap cleavage activi...
MOTIVATION: Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategor...
BACKGROUND AND AIMS: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimi...
To compensate for the lack of touch during minimally invasive and robotic surgeries, tactile sensors are integrated with surgical instruments. Surgica...
Tumor specimens contain a variety of healthy cells as well as cancerous cells, and this heterogeneity underlies resistance to various cancer therapies...
Minimally invasive surgery continues to transform the field of gynecologic oncology and has now become the standard of care for many early-stage malig...
Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspect...
Tumor precision medicine is an emerging approach for tumor diagnosis, treatment and prevention, which takes account of individual variability of envir...
OBJECTIVE Surgical robotics has demonstrated utility across the spectrum of surgery. Robotics in spine surgery, however, remains in its infancy. Here,...
OBJECTIVE The move toward better, more effective optical visualization in the field of neurosurgery has been a focus of technological innovation. In t...
Objective Recent studies have investigated the role of spinal image guidance for pedicle screw placement. Many authors have observed an elevated place...
Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a wide distribution to various species. They can specially iden...
The dramatically increasing high-resolution medical images provide a great deal of useful information for cancer diagnosis, and play an essential role...
We demonstrate that model-based unsupervised learning can uniquely discriminate single-cell subpopulations by their gene expression distributions, whi...
Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incor...
With the rapid development of nanotherapy, concerns surrounding the possible use of nanomaterials-mediated immunomodulation are growing. Thus, evaluat...
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and...
PURPOSE: Accurate segmentation of organs-at-risks (OARs) is the key step for efficient planning of radiation therapy for head and neck (HaN) cancer tr...