Oncology/Hematology

A Hybrid CNN-GLCM Classifier For Detection And Grade Classification Of Brain Tumor.

A supervised CNN Deep net classifier is proposed for the detection, classification and diagnosis of meningioma brain tumor using deep learning approach. This proposed method includes preprocessing, classification, and segmentation of the primary occurring brain tumor in adults. The proposed CNN Deep Net classifier extracts the features internally from the enhanced image and classifies them into no...

Insights into cell classification based on combination of multiple cellular mechanical phenotypes by using machine learning algorithm.

Although cellular elastic property (CEP, also known as cellular elastic modulus) has been frequently reported as a biomarker to distinguish some cancerous cells from their benign counterparts, it cannot be adopted as a universal hallmark to be applied to every kind cell. In the present study, we report that insignificant difference is observed between normal gastric cell and its cancer counterpart...

Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction.

Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most expensive malignancy to treat over the patients' lifetime. In rec...

LeuFeatx: Deep learning-based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear.

The abnormal growth of leukocytes causes hematologic malignancies such as leukemia. The clinical assessment methods for the diagnosis of the disease a...

Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation.

Stereotactic radiosurgery (SRS) is now the standard of care for brain metastases (BMs) patients. The SRS treatment planning process requires precise t...

Light-driven carbon nitride microswimmers with propulsion in biological and ionic media and responsive on-demand drug delivery.

We propose two-dimensional poly(heptazine imide) (PHI) carbon nitride microparticles as light-driven microswimmers in various ionic and biological med...

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model.

Blood cancer has been a growing concern during the last decade and requires early diagnosis to start proper treatment. The diagnosis process is costly...

Big-Hypergraph Factorization Neural Network for Survival Prediction From Whole Slide Image.

Survival prediction for patients based on histopa- thological whole-slide images (WSIs) has attracted increasing attention in recent years. Due to the...

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer.

This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed w...

Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation.

This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for ga...

Deep learning classification of inverted papilloma malignant transformation using 3D convolutional neural networks and magnetic resonance imaging.

BACKGROUND: Distinguishing benign inverted papilloma (IP) tumors from those that have undergone malignant transformation to squamous cell carcinoma (I...

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation do...

Semisupervised Training of a Brain MRI Tumor Detection Model Using Mined Annotations.

Background Artificial intelligence (AI) applications for cancer imaging conceptually begin with automated tumor detection, which can provide the found...

Neural network-enhanced real-time impedance flow cytometry for single-cell intrinsic characterization.

Single-cell impedance flow cytometry (IFC) is emerging as a label-free and non-invasive method for characterizing the electrical properties and reveal...

Integration of gene co-expression analysis and multi-class SVM specifies the functional players involved in determining the fate of HTLV-1 infection toward the development of cancer (ATLL) or neurological disorder (HAM/TSP).

Human T-cell Leukemia Virus type-1 (HTLV-1) is an oncovirus that may cause two main life-threatening diseases including a cancer type named Adult T-ce...

Segmenting pediatric optic pathway gliomas from MRI using deep learning.

Optic pathway gliomas are low-grade neoplastic lesions that account for approximately 3-5% of brain tumors in children. Assessing tumor burden from ma...

A data-driven ultrasound approach discriminates pathological high grade prostate cancer.

Accurate prostate cancer screening is imperative for reducing the risk of cancer death. Ultrasound imaging, although easy, tends to have low resolutio...

Discriminating malignant from benign testicular masses using machine-learning based radiomics signature of appearance diffusion coefficient maps: Comparing with conventional mean and minimum ADC values.

PURPOSE: To develop a machine-learning-based radiomics signature of ADC for discriminating between benign and malignant testicular masses and compare ...

Artificial intelligence for nuclear medicine in oncology.

As in all other medical fields, artificial intelligence (AI) is increasingly being used in nuclear medicine for oncology. There are many articles that...

[Moving towards a personalized oncology: The contribution of genomic techniques and artificial intelligence in the use of circulating tumor biomarkers].

Technological advances, in particular the development of high-throughput sequencing, have led to the emergence of a new generation of molecular biomar...