Lymphoma

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction.

Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer nu...

Large-scale pancreatic cancer detection via non-contrast CT and deep learning.

Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC using a single test remains unfeasible due to the low prevalence and potential harms of false positives. Non-contrast computed tomography (CT), routinely...

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a...

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-recognized. In this study, we optimized the extraction me...

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 coronary calcium scoring using positron emission tomog...

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 the diagnosis of different types of tumor. In the ca...

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-invasive techniques such as resting-state functional ...

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 diagnoses critical for successful treatment. PC c...

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 concurrently explored the influence of multiple m...

The impact of thermal insulating materials in heat loss control in smart green buildings using experimental and swarm intelligent analysis.

The efficacy of saving energy standards depends on the ability to anticipate the heat loss of buildings. Environmentally friendly materials, also know...

Variational quantum algorithm for node embedding.

Quantum machine learning has made remarkable progress in many important tasks. However, the gate complexity of the initial state preparation is seldom...

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using M...

Shedding light on the black box of a neural network used to detect prostate cancer in whole slide images by occlusion-based explainability.

Diagnostic histopathology faces increasing demands due to aging populations and expanding healthcare programs. Semi-automated diagnostic systems emplo...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of p...

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists.

We determined if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to...

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

BACKGROUND: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a...

Comparing pentafecta outcomes between nerve sparing and non nerve sparing robot-assisted radical prostatectomy in a propensity score-matched study.

Pentafecta (continence, potency, cancer control, free surgical margins, and no complications) is an important outcome of prostatectomy. Our objective ...

Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing.

This paper discusses the challenges of producing CAR-T cells for cancer treatment and the potential for Artificial Intelligence (AI) for its improveme...

A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance behavior.

In recent years, identifying road users' behavior and conflicts at intersections have become an essential data source for evaluating traffic safety. A...

AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (...