Oncology/Hematology

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Because of the capacity of tumor antigens to activate the immune response and promote the destruction of tumor cells, they are considered excellent immunotherapeutic drugs. In this work, we evaluated fifteen machine learning algorithms for the classification of tumor antigens. For this purpose, we build r...

A novel gene selection method for gene expression data for the task of cancer type classification.

Cancer is a poligenetic disease with each cancer type having a different mutation profile. Genomic data can be utilized to detect these profiles and to diagnose and differentiate cancer types. Variant calling provide mutation information. Gene expression data reveal the altered cell behaviour. The combination of the mutation and expression information can lead to accurate discrimination of differe...

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System.

At present, human health is threatened by many diseases, and lung cancer is one of the most dangerous tumors that threaten human life. In most develop...

BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells.

BACKGROUND AND OBJECTIVE: The classification of human peripheral blood cells yields significance in the detection of inflammation, infections and bloo...

Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

BACKGROUND AND AIMS: This study aimed to investigate whether AI via a deep learning algorithm using endoscopic ultrasonography (EUS) images could pred...

Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer.

PURPOSE: Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation t...

Artificial intelligence: a critical review of current applications in pancreatic imaging.

The applications of artificial intelligence (AI), including machine learning and deep learning, in the field of pancreatic disease imaging are rapidly...

Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?

PURPOSE: Convolutional neural networks (CNNs) show potential for delineating cancers on contrast-enhanced MRI (ce-MRI) but there are clinical scenario...

Optimizing ANFIS using simulated annealing algorithm for classification of microarray gene expression cancer data.

In the medical field, successful classification of microarray gene expression data is of major importance for cancer diagnosis. However, due to the pr...

Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model's Complexity on Its Processing Speed.

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018...

Antibody Supervised Training of a Deep Learning Based Algorithm for Leukocyte Segmentation in Papillary Thyroid Carcinoma.

The quantity of leukocytes in papillary thyroid carcinoma (PTC) potentially have prognostic and treatment predictive value. Here, we propose a novel m...

Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019.

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer D...

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model.

BACKGROUND AND PURPOSE: Malignant melanoma is an aggressive skin cancer in which brain metastases are common. Our aim was to establish and evaluate a ...

Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey.

Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health ...

[Robot-assisted Distal Pancreatectomy with En Bloc Celiac Axis Resection (Modified Appleby Procedure) after Neoadjuvant Therapy].

Pancreatic carcinoma in the body and on the left side of the mesentericoportal axis is often only detected in late stages owing to unspecific or even ...

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly...

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database.

BACKGROUND: Accurate prognostication is crucial in treatment decisions made for men diagnosed with non-metastatic prostate cancer. Current models rely...

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.

An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occa...

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as D...

Integrating Multi-Omic Data With Deep Subspace Fusion Clustering for Cancer Subtype Prediction.

One type of cancer usually consists of several subtypes with distinct clinical implications, thus the cancer subtype prediction is an important task i...