Oncology/Hematology

A survey on Barrett's esophagus analysis using machine learning.

This work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus (BE) diagnosis and treatment. The use of artificial intelligence is a brand new and promising way to evaluate such disease. We compile some works published at some well-established databases, such as Science Direct, IEEEXplore, PubMed, Plos One, Multidisciplinary Digital Pu...

Robotic Patterning a Superhydrophobic Surface for Collective Cell Migration Screening.

Collective cell migration, in which cells migrate as a group, is fundamental in many biological and pathological processes. There is increasing interest in studying the collective cell migration in high throughput. Cell scratching, insertion blocker, and gel-dissolving techniques are some methodologies used previously. However, these methods have the drawbacks of cell damage, substrate surface alt...

Detecting oropharyngeal carcinoma using multispectral, narrow-band imaging and machine learning.

OBJECTIVE: To determine if multispectral narrow-band imaging (mNBI) can be used for automated, quantitative detection of oropharyngeal carcinoma (OPC)...

Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.

PURPOSE: To develop an automatic deep feature classification (DFC) method for distinguishing benign angiomyolipoma without visible fat (AMLwvf) from m...

Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients.

BACKGROUND AND PURPOSE: Current prognostic models for soft tissue sarcoma (STS) patients are solely based on staging information. Treatment-related da...

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical- Approach Combining Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in ...

Flexible robotic catheters in the visceral segment of the aorta: advantages and limitations.

Flexible robotic catheters are an emerging technology which provide an elegant solution to the challenges of conventional endovascular intervention. O...

A Deep Belief Network and Dempster-Shafer-Based Multiclassifier for the Pathology Stage of Prostate Cancer.

OBJECT: Pathologic prediction of prostate cancer can be made by predicting the patient's prostate metastasis prior to surgery based on biopsy informat...

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly...

ANTENNA, a Multi-Rank, Multi-Layered Recommender System for Inferring Reliable Drug-Gene-Disease Associations: Repurposing Diazoxide as a Targeted Anti-Cancer Therapy.

Existing drug discovery processes follow a reductionist model of "one-drug-one-gene-one-disease," which is inadequate to tackle complex diseases invol...

Chromosome-wide gene dosage rebalance may benefit tumor progression.

The high-risk of tumor initiation in patients with Turner syndrome (TS) characterized by X chromosome monosomy in women has been well established and ...

Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids.

Large-scale application of ionic liquids (ILs) hinges on the advancement of designable and eco-friendly nature. Research of the potential toxicity of ...

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clin...

Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies.

Radiological longitudinal follow-up of tumors in CT scans is essential for disease assessment and liver tumor therapy. Currently, most tumor size meas...

Antiphospholipase 2 receptor antibody levels to predict complete spontaneous remission in primary membranous nephropathy.

BACKGROUND: M-type phospholipase A2 receptor (APLA2R) is considered the major antigen involved in the pathogenesis of adult primary membranous nephrop...

Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends o...

Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning.

Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain st...

Using Big Data Analytics to Advance Precision Radiation Oncology.

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of g...

A Functional Signature Ontology (FUSION) screen detects an AMPK inhibitor with selective toxicity toward human colon tumor cells.

AMPK is a serine threonine kinase composed of a heterotrimer of a catalytic, kinase-containing α and regulatory β and γ subunits. Here we show that in...

High preoperative serum CA 19-9 levels can predict poor oncologic outcomes in colorectal cancer patients on propensity score analysis.

PURPOSE: The purpose of this study is to evaluate the prognostic value of preoperative serum CA 19-9 levels in colorectal cancer patients.