Oncology/Hematology

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer.

This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 breast cancer single-cells treated with the antidiabetic drug metformin. We show that mixture-model-based unsupervised methods with validation from hie...

Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma.

Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease with variations in disease progression and clinical outcomes. The advent of next generation sequencing techniques (NGS) has generated data from patients that can be analysed to develop a predictive model. In this study, we have adopted a machine learning approach to identify biomarkers and build classifiers to discriminate between ea...

Automatic identification of clinically relevant regions from oral tissue histological images for oral squamous cell carcinoma diagnosis.

Identification of various constituent layers such as epithelial, subepithelial, and keratin of oral mucosa and characterization of keratin pearls with...

Network-based association analysis to infer new disease-gene relationships using large-scale protein interactions.

Protein-protein interactions integrated with disease-gene associations represent important information for revealing protein functions under disease c...

Identification of cervical cancer using laser-induced breakdown spectroscopy coupled with principal component analysis and support vector machine.

Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interp...

Optimal dynamic regimens with artificial intelligence: The case of temozolomide.

We determine an optimal protocol for temozolomide using population variability and dynamic optimization techniques inspired by artificial intelligence...

Drug Selection via Joint Push and Learning to Rank.

Selecting the right drugs for the right patients is a primary goal of precision medicine. In this article, we consider the problem of cancer drug sele...

Combined Transarterial Embolization/Chemoembolization-Based Locoregional Treatment with Sorafenib Prolongs the Survival in Patients with Advanced Hepatocellular Carcinoma and Preserved Liver Function: A Propensity Score Matching Study.

BACKGROUND: Sorafenib is the standard treatment for patients with Barcelona Clinic Liver Cancer (BCLC) stage C hepatocellular carcinoma (HCC). However...

Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors.

Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additi...

Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination.

This research aims to address the problem of discriminating benign cysts from malignant masses in breast ultrasound (BUS) images based on Convolutiona...

Advances in the computational and molecular understanding of the prostate cancer cell nucleus.

Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that ...

Robotic Head and Neck Surgery: History, Technical Evolution and the Future.

The first application of robotic technology in surgery was described in 1985 when a robot was used to define the trajectory for a stereotactic brain b...

Effects of nilotinib on platelet function in patients with chronic myeloid leukemia in chronic phase.

BACKGROUND: Tyrosine kinases are highly expressed in platelets and play an important role in their activation process. Some studies have reported the ...

The utilisation of convolutional neural networks in detecting pulmonary nodules: a review.

Lung cancer is one of the leading causes of cancer-related fatality in the world. Patients display few or even no signs or symptoms in the early stage...

Adaptive multinomial regression with overlapping groups for multi-class classification of lung cancer.

Multi-class classification has attracted much attention in cancer diagnosis and treatment and many machine learning methods have emerged for addressin...

Fisher Discrimination Regularized Robust Coding Based on a Local Center for Tumor Classification.

Tumor classification is crucial to the clinical diagnosis and proper treatment of cancers. In recent years, sparse representation-based classifier (SR...

Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.

The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morpho...

Information-Based Medicine in Glioma Patients: A Clinical Perspective.

Glioma constitutes the most common type of primary brain tumor with a dismal survival, often measured in terms of months or years. The thin line betwe...

Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation?

Artificial intelligence (AI) is emerging as a technology with the power to transform established industries, and with applications from automated manu...

Adjuvant Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC) in resected high-risk colon cancer patients - study protocol for the PIPAC-OPC3 Trial. A prospective, controlled phase 2 Study.

BACKGROUND: Peritoneal metastasis (PM) is the second most common site of recurrence in colon cancer (CC) patients and accounts for approximately one-t...