AIMC Topic: Lymph Nodes

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Modeling the covariates effects on the hazard function by piecewise exponential artificial neural networks: an application to a controlled clinical trial on renal carcinoma.

BMC bioinformatics
BACKGROUND: In exploring the time course of a disease to support or generate biological hypotheses, the shape of the hazard function provides relevant information. For long follow-ups the shape of hazard function may be complex, with the presence of ...

Overexpression of EMMPRIN is associated with lymph node metastasis and advanced stage of non-small cell lung cancer: a retrospective study.

BMC pulmonary medicine
BACKGROUND: Previous studies show that overexpression of EMMPRIN involved in the malignant biological behavior of tumors. This investigation was to disclose the expression status of EMMPRIN in non-small cell lung cancer (NSCLC) and its clinical value...

Serum Vitamin D Levels Affect Pathologic Complete Response in Patients Undergoing Neoadjuvant Systemic Therapy for Operable Breast Cancer.

Clinical breast cancer
INTRODUCTION: There has been increasing interest in the potential benefit of vitamin D in improving breast cancer outcome. Preclinical studies suggest that vitamin D enhances chemotherapy-induced cell death. We investigated the impact of serum vitami...

Development of an artificial neural network model for risk assessment of skin sensitization using human cell line activation test, direct peptide reactivity assay, KeratinoSens™ and in silico structure alert parameter.

Journal of applied toxicology : JAT
It is important to predict the potential of cosmetic ingredients to cause skin sensitization, and in accordance with the European Union cosmetic directive for the replacement of animal tests, several in vitro tests based on the adverse outcome pathwa...

Metastasis detection from whole slide images using local features and random forests.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Digital pathology has led to a demand for automated detection of regions of interest, such as cancerous tissue, from scanned whole slide images. With accurate methods using image analysis and machine learning, significant speed-up, and savings in cos...

Prediction of lymph node parasite load from clinical data in dogs with leishmaniasis: An application of radial basis artificial neural networks.

Veterinary parasitology
Quantification of Leishmania infantum load via real-time quantitative polymerase chain reaction (qPCR) in lymph node aspirates is an accurate tool for diagnostics, surveillance and therapeutics follow-up in dogs with leishmaniasis. However, qPCR requ...

Preoperative assessment of lymph node metastasis in endometrial cancer: A Korean Gynecologic Oncology Group study.

Cancer
BACKGROUND: Previously proposed criteria for preoperatively identifying endometrial cancer patients at low risk for lymph node metastasis remain to be verified. For this purpose, a prospective, multicenter observational study was performed.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.

IEEE transactions on medical imaging
Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image fea...