Oncology/Hematology

Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM).

Multiplexed single-cell experimental techniques like mass cytometry measure 40 or more features and enable deep characterization of well-known and novel cell populations. However, traditional data analysis techniques rely extensively on human experts or prior knowledge, and novel machine learning algorithms may generate unexpected population groupings. Marker enrichment modeling (MEM) creates quan...

A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency.

Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained from, e.g., gene expression profile. The majority of machine learning methods suffer from the deficiency of preceding cases, i.e. the gene expression data on patients combined with the confirmed outcome of known treatment methods. At the same time, the...

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic...

Feasibility of predicting tumor motion using online data acquired during treatment and a generalized neural network optimized with offline patient tumor trajectories.

PURPOSE: The accurate prediction of intrafraction lung tumor motion is required to compensate for system latency in image-guided adaptive radiotherapy...

Palliative analgesia with topical sevoflurane in cancer-related skin ulcers: a case report.

A Caucasian 39-year-old male patient with a poorly-differentiated infiltrating epidermoid penile carcinoma with urethral invasion was diagnosed. The p...

Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways.

The war on cancer is progressing globally but slowly as researchers around the world continue to seek and discover more innovative and effective ways ...

Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods.

The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM). Ga-Pentixafor PET/CT can capture the abnormal mol...

Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features.

Liver is the heaviest internal organ of the human body and performs many vital functions. Prolonged cirrhosis and fatty liver disease may lead to the ...

A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.

Cancers that appear pathologically similar often respond differently to the same drug regimens. Methods to better match patients to drugs are in high ...

Support vector machine classifier for prediction of the metastasis of colorectal cancer.

Colorectal cancer (CRC) is one of the most common cancers and a major cause of mortality. The present study aimed to identify potential biomarkers for...

Cockcroft-Gault, Modification of Diet in Renal Disease, and Chronic Kidney Disease Epidemiology Collaboration equations for estimating glomerular filtration rates in cancer patients receiving cisplatin-based chemotherapy.

BACKGROUND: Although the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation has been recommended for accurate estimates of glomerula...

Cytotoxic, Apoptotic and Genotoxic Effects of Lipid-Based and Polymeric Nano Micelles, an In Vitro Evaluation.

Self-assembly systems (SAS) mainly consist of micelles, and liposomes are the classes of Nano Drug Delivery Systems with superior properties compared ...

Comparison of Changes in the Lipid Profiles of Eastern Chinese Postmenopausal Women With Early-Stage Breast Cancer Treated With Different Aromatase Inhibitors: A Retrospective Study.

Cardiovascular morbidity is closely associated with serum lipid level. We aimed to investigate the effects of different aromatase inhibitors, includin...

Analogous detection of circulating tumor cells using the AccuCyte -CyteFinder system and ISET system in patients with locally advanced and metastatic prostate cancer.

INTRODUCTION: Circulating tumor cells (CTCs) can provide important information on patient's prognosis and treatment efficacy. Currently, a plethora of...

Inflammatory bowel disease patients experiencing a loss of response to infliximab regain long-term response after undergoing granulocyte/monocyte apheresis: A case series.

Up to 50% of patients with ulcerative colitis (UC) or Crohn's disease (CD) experience a loss of response (LOR) to infliximab after an initial response...

Outcomes and toxicity from a prospective study of moderately hypofractionated radiation therapy for prostate cancer.

PURPOSE: The purpose of this study is to report the long-term outcomes and toxicity results of a prospective trial of moderately hypofractionated, ima...

Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification.

Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues...

Prognostic values of the integrated model incorporating the volume of metastatic regional cervical lymph node and pretreatment serum Epstein-Barr virus DNA copy number in predicting distant metastasis in patients with N1 nasopharyngeal carcinoma.

BACKGROUND: According to the 7th edition of the American Joint Committee on Cancer (AJCC) staging system, over 50% of patients with nasopharyngeal car...

L1 Cell Adhesion Molecule and Its Soluble Form sL1 Exhibit Poor Prognosis in Primary Breast Cancer Patients.

INTRODUCTION: The L1 cell adhesion molecule (L1-CAM) and its soluble form sL1 play a prominent role in invasion and metastasis in several cancers. How...

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structur...