Lymphoma

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging.

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisition...

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic features to diagnose cervical LNM in patients with NSCLC.

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.

Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualiz...

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated ...

Boosting predictive models and augmenting patient data with relevant genomic and pathway information.

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized ca...

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel d...

Machine learning-based pathomics signature of histology slides as a novel prognostic indicator in primary central nervous system lymphoma.

PURPOSE: To develop and validate a pathomics signature for predicting the outcomes of Primary Central Nervous System Lymphoma (PCNSL).

Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.

Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is importa...

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass sp...

Machine learning-based analysis of Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.

Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes. Since the tissue sampling procedures are invasive...

Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remai...

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convo...

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance im...

Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction.

The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is crucial for...

An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI.

Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susce...

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction.

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we und...

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually...

Optimal Enzyme-Assisted Extraction of Phenolics from Leaves of Pongamia pinnata via Response Surface Methodology and Artificial Neural Networking.

This research work seeks to evaluate the impact of selected enzyme complexes on the optimised release of phenolics from leaves of Pongamia pinnata. Af...

Artificial intelligence-enabled optimization of Fe/Zn@biochar photocatalyst for 2,6-dichlorophenol removal from petrochemical wastewater: A techno-economic perspective.

While numerous studies have addressed the photocatalytic degradation of 2,6-dichlorophenol (2,6-DCP) in wastewater, an existing research gap pertains ...

Attenuation correction and truncation completion for breast PET/MR imaging using deep learning.

. Simultaneous PET/MR scanners combine the high sensitivity of MR imaging with the functional imaging of PET. However, attenuation correction of breas...