Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Additional filters

Article Language

Species

Sex

Age

Other

Search Results

5 results

Filters applied: . Clear all
Results are displayed in a computed author sort order. The Publication Date timeline is not available.
Page 1
Automated real-world data integration improves cancer outcome prediction.
Jee J, Fong C, Pichotta K, Tran TN, Luthra A, Waters M, Fu C, Altoe M, Liu SY, Maron SB, Ahmed M, Kim S, Pirun M, Chatila WK, de Bruijn I, Pasha A, Kundra R, Gross B, Mastrogiacomo B, Aprati TJ, Liu D, Gao J, Capelletti M, Pekala K, Loudon L, Perry M, Bandlamudi C, Donoghue M, Satravada BA, Martin A, Shen R, Chen Y, Brannon AR, Chang J, Braunstein L, Li A, Safonov A, Stonestrom A, Sanchez-Vela P, Wilhelm C, Robson M, Scher H, Ladanyi M, Reis-Filho JS, Solit DB, Jones DR, Gomez D, Yu H, Chakravarty D, Yaeger R, Abida W, Park W, O'Reilly EM, Garcia-Aguilar J, Socci N, Sanchez-Vega F, Carrot-Zhang J, Stetson PD, Levine R, Rudin CM, Berger MF, Shah SP, Schrag D, Razavi P, Kehl KL, Li BT, Riely GJ, Schultz N; MSK Cancer Data Science Initiative Group. Jee J, et al. Among authors: pichotta k. Nature. 2024 Nov 6. doi: 10.1038/s41586-024-08167-5. Online ahead of print. Nature. 2024. PMID: 39506116
DNA liquid biopsy-based prediction of cancer-associated venous thromboembolism.
Jee J, Brannon AR, Singh R, Derkach A, Fong C, Lee A, Gray L, Pichotta K, Luthra A, Diosdado M, Haque M, Guo J, Hernandez J, Garg K, Wilhelm C, Arcila ME, Pavlakis N, Clarke S, Shah SP, Razavi P, Reis-Filho JS, Ladanyi M, Schultz N, Zwicker J, Berger MF, Li BT, Mantha S. Jee J, et al. Among authors: pichotta k. Nat Med. 2024 Sep;30(9):2499-2507. doi: 10.1038/s41591-024-03195-0. Epub 2024 Aug 15. Nat Med. 2024. PMID: 39147831 Free PMC article.
Fast, light, and scalable: harnessing data-mined line annotations for automated tumor segmentation on brain MRI.
Swinburne NC, Yadav V, Murthy KNK, Elnajjar P, Shih HH, Panyam PK, Santilli A, Gutman DC, Pike L, Moss NS, Stone J, Hatzoglou V, Shah A, Juluru K, Shah SP, Holodny AI, Young RJ; M.S.K. MIND Consortium. Swinburne NC, et al. Eur Radiol. 2023 Sep;33(9):6582-6591. doi: 10.1007/s00330-023-09583-3. Epub 2023 Apr 12. Eur Radiol. 2023. PMID: 37042979 Free PMC article.
Semisupervised Training of a Brain MRI Tumor Detection Model Using Mined Annotations.
Swinburne NC, Yadav V, Kim J, Choi YR, Gutman DC, Yang JT, Moss N, Stone J, Tisnado J, Hatzoglou V, Haque SS, Karimi S, Lyo J, Juluru K, Pichotta K, Gao J, Shah SP, Holodny AI, Young RJ; MSK MIND Consortium. Swinburne NC, et al. Among authors: pichotta k. Radiology. 2022 Apr;303(1):80-89. doi: 10.1148/radiol.210817. Epub 2022 Jan 18. Radiology. 2022. PMID: 35040676 Free PMC article.