Lymphoma

Artificial intelligence-based analysis of time-lapse images of sphere formation and process of plate adhesion and spread of pancreatic cancer cells.

Most pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC). Spherical morphology formed i...

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune...

Pinobanksin from peony seed husk: A flavonoid with the potential to inhibit the proliferation of SH-SY5Y.

Pinobanksin, as one of the flavonoids, has powerful biological activities but has been under-recogni...

Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.

OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coro...

CHARACTERISATION OF RESORBABLE AND NON- RESORBABLE SUTURES COATED WITH Punica granatum SEED EXTRACT: AN in vitro PILOT STUDY.

BACKGROUND: In order to achieve uneventful and rapid healing of the tissues, a suture material shoul...

Non-fragile output-feedback control for time-delay neural networks with persistent dwell time switching: A system mode and time scheduler dual-dependent design.

This paper is concerned with non-fragile output-feedback control for time-delay neural networks with...

Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach.

Localization of early infarction on first-line Non-contrast computed tomogram (NCCT) guides prompt t...

Histological classification of canine and feline lymphoma using a modular approach based on deep learning and advanced image processing.

Histopathological examination of tissue samples is essential for identifying tumor malignancy and th...

MDSR-NMF: Multiple deconstruction single reconstruction deep neural network model for non-negative matrix factorization.

Dimension reduction is one of the most sought-after strategies to cope with high-dimensional ever-ex...

Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning.

PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-inv...

Patterns of Simultaneous and non-Simultaneous Use of Cannabis and Alcohol Among American Indian Adolescents.

BACKGROUND: American Indian (AI) adolescents report earlier initiation and higher rates of cannabis ...

CT scan pancreatic cancer segmentation and classification using deep learning and the tunicate swarm algorithm.

Pancreatic cancer (PC) is a very lethal disease with a low survival rate, making timely and accurate...

A Deep-Learning Model for Predicting the Efficacy of Non-vascularized Fibular Grafting Using Digital Radiography.

RATIONALE AND OBJECTIVES: To develop a fully automated deep-learning (DL) model using digital radiog...

Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Recent research in drug discovery dealing with many faces difficulties, including development of new...

An integrated model combined intra- and peritumoral regions for predicting chemoradiation response of non small cell lung cancers based on radiomics and deep learning.

PURPOSE: The purpose of this study was to develop a model for predicting chemoradiation response in ...

Non-invasive detection of anemia using lip mucosa images transfer learning convolutional neural networks.

Anemia is defined as a drop in the number of erythrocytes or hemoglobin concentration below normal l...

Early MS Identification Using Non-linear Functional Connectivity and Graph-theoretic Measures of Cognitive Task-fMRI Data.

INTRODUCTION: Functional neuroimaging has developed a fundamental ground for understanding the physi...

A machine learning approach to identify important variables for distinguishing between fallers and non-fallers in older women.

Falls are a significant ongoing public health concern for older adults. At present, few studies have...

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example.

Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to ...

LSTM4piRNA: Efficient piRNA Detection in Large-Scale Genome Databases Using a Deep Learning-Based LSTM Network.

Piwi-interacting RNAs (piRNAs) are a new class of small, non-coding RNAs, crucial in the regulation ...

Natural language processing tools for non-clinical healthcare management.