Oncology/Hematology

[Diagnosis of malignant pleural effusions using convolutional neural networks by the morphometric image analysis of facies of pleural exudate].

OBJECTIVE: To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.

[Artificial intelligence-guided precision medicine in hematological disorders].

Precision medicine in oncology uses genomic data to provide the right intervention in the right patients at the right time. For this purpose, next-generation sequencing (NGS) is an indispensable tool. However, further innovations are necessary, including medical informatics which uses somatic mutations to inform clinical intervention. This process, called manual interpretation or curation, is curr...

Identification of Cancer Biomarkers in Human Body Fluids by Using Enhanced Physicochemical-incorporated Evolutionary Conservation Scheme.

OBJECTIVE: Cancer is one of the most serious diseases affecting human health. Among all current cancer treatments, early diagnosis and control signifi...

A Survey on Machine Learning Algorithms for the Diagnosis of Breast Masses with Mammograms.

Breast cancer is leading cancer among women for the past 60 years. There are no effective mechanisms for completely preventing breast cancer. Rather i...

Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.

BACKGROUND: Breast cancer is one of the most leading causes of cancer deaths among women. Early detection of cancer increases the survival rate of the...

SDResU-Net: Separable and Dilated Residual U-Net for MRI Brain Tumor Segmentation.

BACKGROUND: Glioma is one of the most common and aggressive primary brain tumors that endanger human health. Tumors segmentation is a key step in assi...

Radiomics and artificial Intelligence for PET imaging analysis.

In recent years, processing of the imaging signal derived from CT, MR or positron emission has proven to be able to predict outcome parameters in canc...

Automated Intensity Modulated Radiation Therapy Treatment Planning for Cervical Cancer Based on Convolution Neural Network.

PURPOSE: To develop and evaluate an automatic intensity-modulated radiation therapy (IMRT) program for cervical cancer, including a Convolution Neural...

A Review of Various Machine Learning Techniques for Brain Tumor Detection from MRI Images.

BACKGROUND: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based...

Predicting Peritoneal Metastasis of Gastric Cancer Patients Based on Machine Learning.

OBJECTIVE: The aim is to explore the prediction effect of 5 machine learning algorithms on peritoneal metastasis of gastric cancer.

Diterpenoids from Roots of and Toxicity against Human Cancer Cell Lines.

Further investigations on phytochemical constituents of dichloromethane extract from roots of ( led to the isolation and identification of eight know...

Mediated Synthesis of Silver Nanoparticles and Its Evaluation of Antineoplastic Activity to Combat Colorectal Cancer Cell Line.

Several formulations of herbal plants have been extensively applied to treat diseases. ( is an Iranian traditional plant with a wide range of benefit...

Comparative Study in Efficacy and Safety of Intralesional Injections of Vitamin D3, Measles Rubella (MR) Vaccine, and Purified Protein Derivative (PPD) in the Management of Cutaneous Warts.

INTRODUCTION: Cutaneous warts caused by human papillomavirus are the most common dermatological diseases being contagious, recurrent, and recalcitrant...

LOCALIZATION OF IONIZING RADIATION SOURCES VIA AN AUTONOMOUS ROBOTIC SYSTEM.

The article discusses an autonomous and flexible robotic system for radiation monitoring. The detection part of the system comprises two NaI(Tl) scint...

Deep Learning Reveals Cancer Metastasis and Therapeutic Antibody Targeting in the Entire Body.

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long be...

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database ...

Establishment and application of an artificial intelligence diagnosis system for pancreatic cancer with a faster region-based convolutional neural network.

BACKGROUND: Early diagnosis and accurate staging are important to improve the cure rate and prognosis for pancreatic cancer. This study was performed ...

Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer.

BACKGROUND: Artificial intelligence-assisted image recognition technology is currently able to detect the target area of an image and fetch informatio...

Development and Assessment of a Machine Learning Model to Help Predict Survival Among Patients With Oral Squamous Cell Carcinoma.

IMPORTANCE: Predicting survival of oral squamous cell carcinoma through the use of prediction modeling has been underused, and the development of pred...

Applications of artificial intelligence in neuro-oncology.

PURPOSE OF REVIEW: To discuss recent applications of artificial intelligence within the field of neuro-oncology and highlight emerging challenges in i...