Hematology

Lymphoma

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

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Prediction of early recurrence in primary central nervous system lymphoma based on multimodal MRI-based radiomics: A preliminary study.

OBJECTIVES: To evaluate the role of multimodal magnetic resonance imaging radiomics features in pred...

Updated perspectives on visceral pleural invasion in non-small cell lung cancer: A propensity score-matched analysis of the SEER database.

BACKGROUND: Visceral pleural invasion (VPI), including PL1 (the tumor invades beyond the elastic lay...

The phase-seeding method for solving non-centrosymmetric crystal structures: a challenge for artificial intelligence.

The overall crystallographic process involves acquiring experimental data and using crystallographic...

Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.

Diabetes is a growing global health concern, affecting millions and leading to severe complications ...

AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma.

BACKGROUND: Lymphoma is a malignant tumor of the immune system and its incidence is increasing year ...

Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments.

Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road ...

Prediction of postoperative intensive care unit admission with artificial intelligence models in non-small cell lung carcinoma.

BACKGROUND: There is no standard practice for intensive care admission after non-small cell lung can...

UGV-NBWASTE: An oriented dataset for non-biodegradable waste in Bangladesh.

The "UGV-NBWASTE" dataset is built for those who manage non-biodegradable waste. The selection of no...

Deep Learning Approach Readily Differentiates Papilledema, Non-Arteritic Anterior Ischemic Optic Neuropathy, and Healthy Eyes.

OBJECTIVE: Deep learning (DL) has been used in differentiating a range of ophthalmic conditions. We ...

Using the counterfactual framework to estimate non-intention-to-treat estimands in randomised controlled trials: A methodological scoping review.

BACKGROUND: Randomised controlled trials (RCTs) commonly estimate intention-to-treat (ITT) estimands...

DruGagent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction.

Advancements in large language models (LLMs) allow them to address diverse questions using human-lik...

Prioritization strategies for non-target screening in environmental samples by chromatography - High-resolution mass spectrometry: A tutorial.

Non-target screening (NTS) using chromatography coupled to high-resolution mass spectrometry (HRMS),...

Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network.

Neonatal jaundice, characterized by elevated bilirubin levels causing yellow discoloration of the sk...

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