Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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Memory efficient model based deep learning reconstructions for high spatial resolution 3D non-cartesian acquisitions.

. Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Car...

Parallelized ultrasound homodyned-K imaging based on a generalized artificial neural network estimator.

The homodyned-K (HK) distribution model is a generalized backscatter envelope statistical model for ...

Robot-assisted thoracic surgery for stages IIB-IVA non-small cell lung cancer: retrospective study of feasibility and outcome.

Robot-assisted thoracic surgery (RATS) for higher stages non-small cell lung carcinoma (NSCLC) remai...

Tritium: Its relevance, sources and impacts on non-human biota.

Tritium (H) is a radioactive isotope of hydrogen that is abundantly released from nuclear industries...

A machine learning based approach for quantitative evaluation of cell migration in Transwell assays based on deformation characteristics.

Many pathological and physiological processes, including embryonic development, immune response and ...

A deep graph convolutional neural network architecture for graph classification.

Graph Convolutional Networks (GCNs) are powerful deep learning methods for non-Euclidean structure d...

Non-invasive regional cerebral blood flow quantification in the 123I-IMP autoradiography using artificial neural network.

PURPOSE: Regional cerebral blood flow (rCBF) quantification using 123I-N-isopropyl-p-iodoamphetamine...

The promise and peril of interactive embodied agents for studying non-verbal communication: a machine learning perspective.

In face-to-face interactions, parties rapidly react and adapt to each other's words, movements and e...

Differentiating Glaucomatous Optic Neuropathy From Non-glaucomatous Optic Neuropathies Using Deep Learning Algorithms.

PURPOSE: A deep learning framework to differentiate glaucomatous optic disc changes due to glaucomat...

ncDENSE: a novel computational method based on a deep learning framework for non-coding RNAs family prediction.

BACKGROUND: Although research on non-coding RNAs (ncRNAs) is a hot topic in life sciences, the funct...

Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognostication.

BACKGROUND AND OBJECTIVE: Deep learning is applied in medicine mostly due to its state-of-the-art pe...

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

In order to treat degenerative diseases, the importance of advanced therapy medicinal products has i...

Deep learning ensemble 2D CNN approach towards the detection of lung cancer.

In recent times, deep learning has emerged as a great resource to help research in medical sciences....

Single-cell RNA-seq data analysis based on directed graph neural network.

Single-cell RNA sequencing (scRNA-seq) data scale surges with high-throughput sequencing technology ...

Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence.

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interve...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from s...

Operational parameter prediction of electrocoagulation system in a rural decentralized water treatment plant by interpretable machine learning model.

Electrocoagulation (EC) is a promising alternative for decentralized drinking water treatment in rur...

Deep learning model integrating positron emission tomography and clinical data for prognosis prediction in non-small cell lung cancer patients.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of lun...

Modelling vegetation land fragmentation in urban areas of Western Province, Sri Lanka using an Artificial Intelligence-based simulation technique.

Vegetation land fragmentation has had numerous negative repercussions on sustainable development aro...

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown th...

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