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Cancer insights from magnetic resonance spectroscopy of cells and excised tumors.

NMR in biomedicine
Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to...

Detection of Benign and Malignant Tumors in Skin Empowered with Transfer Learning.

Computational intelligence and neuroscience
Skin cancer is a major type of cancer with rapidly increasing victims all over the world. It is very much important to detect skin cancer in the early stages. Computer-developed diagnosis systems helped the physicians to diagnose disease, which allow...

A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study.

Journal of medical Internet research
BACKGROUND: Information in pathology reports is critical for cancer care. Natural language processing (NLP) systems used to extract information from pathology reports are often narrow in scope or require extensive tuning. Consequently, there is growi...

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Radiomics and deep learning have emerged as two distinct approaches to medical image analysis. However, their relative expressive power remains largely unknown. Theoretically, hand-crafted radiomic features represent a mere ...

Deep learning-based attenuation correction for whole-body PET - a multi-tracer study with F-FDG,  Ga-DOTATATE, and F-Fluciclovine.

European journal of nuclear medicine and molecular imaging
UNLABELLED: A novel deep learning (DL)-based attenuation correction (AC) framework was applied to clinical whole-body oncology studies using F-FDG,  Ga-DOTATATE, and F-Fluciclovine. The framework used activity (λ-MLAA) and attenuation (µ-MLAA) maps e...

High-Precision Intelligent Cancer Diagnosis Method: 2D Raman Figures Combined with Deep Learning.

Analytical chemistry
Raman spectroscopy, as a label-free detection technology, has been widely used in tumor diagnosis. However, most tumor diagnosis procedures utilize multivariate statistical analysis methods for classification, which poses a major bottleneck toward ac...

Long short-term memory model - A deep learning approach for medical data with irregularity in cancer predication with tumor markers.

Computers in biology and medicine
BACKGROUND: Machine learning (ML) has emerged as a superior method for the analysis of large datasets. Application of ML is often hindered by incompleteness of the data which is particularly evident when approaching disease screening data due to vari...

Performance Analysis of Deep Learning Models for Binary Classification of Cancer Gene Expression Data.

Journal of healthcare engineering
The classification of patients as cancer and normal patients by applying the computational methods on their gene expression profiles is an extremely important task. Recently, deep learning models, mainly multilayer perceptron and convolutional neural...

iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...