Oncology/Hematology

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions.

Identification of topological features in renal tumor microenvironment associated with patient survival.

MOTIVATION: As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However, traditional qualitative and/or semi-quantitative parameters obtained by pathologist's visual examination have very limited capability to capture this interaction between tumor an...

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prost...

Convolutional Invasion and Expansion Networks for Tumor Growth Prediction.

Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion eq...

Breast cancer tumor type recognition using graph feature selection technique and radial basis function neural network with optimal structure.

CONTEXT: Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate i...

Short-term outcomes in patients with colon cancer treated with robotic right colectomy.

PURPOSE: To report a single surgeon series of consecutive robotic right colectomies (RRC) performed for non-metastatic right colon cancer.

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported ...

MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks.

Glioblastoma Multiforme (GBM), a malignant brain tumor, is among the most lethal of all cancers. Temozolomide is the primary chemotherapy treatment fo...

On the Fuzziness of Machine Learning, Neural Networks, and Artificial Intelligence in Radiation Oncology.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification...

Machine Learning Enables Live Label-Free Phenotypic Screening in Three Dimensions.

There is a large amount of information in brightfield images that was previously inaccessible by using traditional microscopy techniques. This informa...

Robot-Assisted Versus Laparoscopy-Assisted Proximal Gastrectomy for Early Gastric Cancer in the Upper Location: Comparison of Oncological Outcomes, Surgical Stress, and Nutritional Status.

BACKGROUND: An increasing amount of attention has been paid to minimally invasive function-preserving gastrectomy, with an increase in incidence of ea...

Predicting Clinical Outcomes in Colorectal Cancer Using Machine Learning.

Using gene markers and other patient features to predict clinical outcomes plays a vital role in enhancing clinical decision making and improving prog...

An Automated Technique to Construct a Knowledge Base of Traditional Chinese Herbal Medicine for Cancers: An Exploratory Study for Breast Cancer.

Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and...

Radiation Oncology Terminology Linker: A Step Towards a Linked Data Knowledge Base.

Performing image feature extraction in radiation oncology is often dependent on the organ and tumor delineations provided by clinical staff. These del...

Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Rece...

A Brief Survey of Machine Learning Application in Cancerlectin Identification.

Proteins with at least one carbohydrate recognition domain are lectins that can identify and reversibly interact with glycan moiety of glycoconjugates...

A comparison of logistic regression and artificial neural networks in predicting central lymph node metastases in papillary thyroid microcarcinoma.

OBJECTIVE: Prophylactic central lymph node dissection(CLND) is a controversial issue in papillary thyroid microcarcinoma( PTMC) patients without lymph...

[RETROPERITONEAL LIPOSARCOMA WITH MULTIPLE RECURRENCE OF LUNG METASTASES TREATED BY MULTIMODAL THERAPY CENTERING ON THE OPERATION: A CASE REPORT].

A 34-year-old man presented with scrotal pain and slight fever. The scrotal pain was improved by the treatment of antibiotics, but the slight fever re...

Overview of the Biological Activities of a Methanol Extract from Wild Red Belt Conk, Fomitopsis pinicola (Agaricomycetes), Fruiting Bodies from Central Italy.

Fomitopsis pinicola (Sw.) P. Karst. (Fomitopsidaceae) is a medicinal mushroom with a variety of healthy properties. In this study we tested the radica...