Oncology/Hematology

Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis.

Digitizing whole-slide imaging in digital pathology has led to the advancement of computer-aided tissue examination using machine learning techniques, especially convolutional neural networks. A number of convolutional neural network-based methodologies have been proposed to accurately analyze histopathological images for cancer detection, risk prediction, and cancer subtype classification. Most e...

Early Prediction of Single-Cell Derived Sphere Formation Rate Using Convolutional Neural Network Image Analysis.

Functional identification of cancer stem-like cells (CSCs) is an established method to identify and study this cancer subpopulation critical for cancer progression and metastasis. The method is based on the unique capability of single CSCs to survive and grow to tumorspheres in harsh suspension culture environment. Recent advances in microfluidic technology have enabled isolating and culturing tho...

Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach.

BACKGROUND: Previous attempts to identify predictors of treatment outcomes in body dysmorphic disorder (BDD) have yielded inconsistent findings. One w...

A closer look to the new frontier of artificial intelligence in the percutaneous treatment of primary lesions of the liver.

The purpose of thermal ablation is induction of tumor death by means of localized hyperthermia resulting in irreversible cellular damage. Ablative the...

Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas.

BACKGROUND: Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find...

What's new in IBD therapy: An "omics network" approach.

The industrial revolution that began in the late 1800s has resulted in dramatic changes in the environment, human lifestyle, dietary habits, social st...

A computer-aided diagnosis system for brain magnetic resonance imaging images using a novel differential feature neural network.

To improve the performance of brain tumor diagnosis, numerous automatic brain tumor diagnosis systems that use machine learning technologies have been...

Deep Learning model for markerless tracking in spinal SBRT.

Stereotactic Body Radiation Therapy (SBRT), alternatively termed Stereotactic ABlative Radiotherapy (SABR) or Stereotactic RadioSurgery (SRS), deliver...

Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods.

Globally, cervical cancer remains as the foremost prevailing cancer in females. Hence, it is necessary to distinguish the importance of risk factors o...

3D-MCN: A 3D Multi-scale Capsule Network for Lung Nodule Malignancy Prediction.

Despite the advances in automatic lung cancer malignancy prediction, achieving high accuracy remains challenging. Existing solutions are mostly based ...

RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning.

PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) me...

RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes.

Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins, ionizing water molecules to produce toxic free r...

Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole-slide images.

BACKGROUND: It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patien...

Generative approach for data augmentation for deep learning-based bone surface segmentation from ultrasound images.

PURPOSE: Precise localization of cystic bone lesions is crucial for osteolytic bone tumor surgery. Recently, there is a move toward ultrasound imaging...

Intelligent classification of platelet aggregates by agonist type.

Platelets are anucleate cells in blood whose principal function is to stop bleeding by forming aggregates for hemostatic reactions. In addition to the...

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies.

Prostate cancer (PrCa) is the second most common cancer among men in the United States. The gold standard for detecting PrCa is the examination of pro...

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and fu...

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in track...

Predicting cancer origins with a DNA methylation-based deep neural network model.

Cancer origin determination combined with site-specific treatment of metastatic cancer patients is critical to improve patient outcomes. Existing path...

A primer on artificial intelligence and its application to endoscopy.

Artificial intelligence (AI) has emerged as a powerful and exciting new technology poised to impact many aspects of health care. In endoscopy, AI is n...