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researcher

J. Stember

10 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author8
  • last author1

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.NE3
  • cs.AI1
  • eess.IV1
  • q-bio.QM1

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedDeep reinforcement learning to detect brain lesions on MRI: a proof-of-concept application of reinforcement learning to medical images

6 citations · 12 across the 8 of their papers we have counts for

collaborators
Showing cs.NEShow all

3 papers · 1 filter

cs.NE2022

Deep neuroevolution to predict primary brain tumor grade from functional MRI adjacency matrices

Joseph Stember, Mehrnaz Jenabi, Luca Pasquini +3

Whereas MRI produces anatomic information about the brain, functional MRI (fMRI) tells us about neural activity within the brain, including how various regions communicate with eac…

cs.NE2022

Deep neuroevolution for limited, heterogeneous data: proof-of-concept application to Neuroblastoma brain metastasis using a small virtual pooled image collection

Subhanik Purkayastha, Hrithwik Shalu, David Gutman +6

Artificial intelligence (AI) in radiology has made great strides in recent years, but many hurdles remain. Overfitting and lack of generalizability represent important ongoing chal…

cs.NE2022★ 1 cited

Direct evaluation of progression or regression of disease burden in brain metastatic disease with Deep Neuroevolution

Joseph Stember, Robert Young, Hrithwik Shalu

Purpose: A core component of advancing cancer treatment research is assessing response to therapy. Doing so by hand, for example as per RECIST or RANO criteria, is tedious, time-co…

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