December 8, 2025BloodOpen Access

Follicular disorganization of the spleen in sickle cell disease identified by a convolutional neural network model

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Authors

ASAdam T. SzafranHouston Advanced Research Center NENorma EstradaVall d'Hebron Hospital Universitari CCCholadda V. CurryTexas Children's Hospital

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Implication

Experimental analysis using a convolutional neural network reveals altered immune cell patterns in spleens of sickle cell disease patients, suggesting immune dysregulation.

Key Points

Follicular disorganization observed in spleens of patients with sickle cell disease points to immune dysfunction.
Pathology results indicated a significant increase in certain immune cell markers compared to controls.
Analysis involved high-resolution imaging and a convolutional neural network, enhancing identification precision.
Findings support the need for further research to explore immune mechanisms related to sickle cell disease.

Cite This Study

Szafran et al. (2025) studied this question.

synapsesocial.com/papers/69362f7d4fa91c937236e48d https://doi.org/10.1182/blood-2025-1159

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Implication

Experimental analysis using a convolutional neural network reveals altered immune cell patterns in spleens of sickle cell disease patients, suggesting immune dysregulation.

Follicular disorganization of the spleen in sickle cell disease identified by a convolutional neural network model

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Implication

Key Points

Cite This Study

Follicular disorganization of the spleen in sickle cell disease identified by a convolutional neural network model

Discussion

Member takes

Implication

Key Points

Cite This Study

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