Oncology/Hematology

Gaussian process classification of superparamagnetic relaxometry data: Phantom study.

MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIONs) enables the reconstruction of SPIONs spatial distribution and hence tumor detection. However, image reconstruction often requires solving an ill-p...

Biological activities of plant extracts from and : An antimalarial, antitrypanosomal and cytotoxity evaluation.

The cytotoxic, antiplasmodial, and antitrypanosomal activities of two medicinal plants traditionally used in Cameroon were evaluated. Wood of Roxb. ex Hornem. aerial roots (Moraceae) and Spring (Selaginellaceae) leaves were collected from two different sites in Cameroon. cell-growth inhibition activities were assessed on methanol extract of plant materials against strain 3D7 and , as well as a...

A liquid chromatography with tandem mass spectrometry method for quantitating total and unbound ceritinib in patient plasma and brain tumor.

A rapid, sensitive, and robust reversed-phase liquid chromatography with tandem mass spectrometry method was developed and validated for the determina...

Renal recovery after severe acute kidney injury in critically ill myeloma patients: a retrospective study.

BACKGROUND: Despite substantial improvements in the management of multiple myeloma, renal failure remains an important burden that tremendously impair...

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

Multiparametric Magnetic Resonance Imaging (MRI) can provide detailed information of the physical characteristics of rectum tumours. Several investiga...

Synthesis and Biological Evaluations of Ring Substituted Tetrahydroisoquinolines (THIQs) as Anti-Breast Cancer Agents.

Breast cancer is a leading cause of mortality among women, resulting in more than half a million deaths worldwide every year. Although chemotherapeuti...

Outcomes of combination MRI-targeted and transperineal template biopsy in restaging low-risk prostate cancer for active surveillance.

OBJECTIVE: Active surveillance (AS) offers a strategy to reduce overtreatment and now is a widely accepted treatment option for low-risk prostate canc...

PAK6-Associated Support Vector Machine Classifier: A New Way to Evaluate Response and Survival of Gastric Cancer Treated by 5-FU/Oxaliplatin Chemotherapy.

ISOWN: accurate somatic mutation identification in the absence of normal tissue controls.

BACKGROUND: A key step in cancer genome analysis is the identification of somatic mutations in the tumor. This is typically done by comparing the geno...

Prostate-Specific Membrane Antigen Positron Emission Tomography-Computed Tomography for Prostate Cancer: Distribution of Disease and Implications for Radiation Therapy Planning.

PURPOSE: To explore the prostate-specific membrane antigen (PSMA)-avid distribution of prostate cancer (PC) on positron emission tomography (PET), bot...

A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation.

Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes involved in breast cancer c...

Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model.

Automated breast cancer multi-classification from histopathological images plays a key role in computer-aided breast cancer diagnosis or prognosis. Br...

Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy.

PURPOSE: Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, dise...

Long-term survival after surveillance and treatment in patients with chronic viral hepatitis and hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the main cause of mortality in patients with chronic viral hepatitis (CVH). We determined the impact of surveillance...

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning meth...

AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue.

In prognostic evaluation of breast cancer Immunohistochemical (IHC) markers namely, oestrogen receptor (ER) and progesterone receptor (PR) are widely ...

An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer sc...

Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma.

We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal c...

Integration of data mining classification techniques and ensemble learning to identify risk factors and diagnose ovarian cancer recurrence.

Ovarian cancer is the second leading cause of deaths among gynecologic cancers in the world. Approximately 90% of women with ovarian cancer reported h...

Mesenteric approach during pancreaticoduodenectomy for pancreatic ductal adenocarcinoma.

Mesenteric approach is an artery-first approach during pancreaticoduodenectomy (PD). In the present study, we evaluated clinical and oncological benef...