Brain is also time: good short-term outcome predictions of artificial intelligence in spontaneous intracerebral hemorrhage pave the way for the long-term assessment
European Radiology - 2024
Tóm tắt
Từ khóa
Tài liệu tham khảo
Safatli DA, Gunther A, Schlattmann P, Schwarz F, Kalff R, Ewald C (2016) Predictors of 30-day mortality in patients with spontaneous primary intracerebral hemorrhage. Surg Neurol Int 7:S510-517. https://doi.org/10.4103/2152-7806.187493
Al-Mufti F, Thabet AM, Singh T, El-Ghanem M, Amuluru K, Gandhi CD (2018) Clinical and radiographic predictors of intracerebral hemorrhage outcome. Interv Neurol 7:118–136. https://doi.org/10.1159/000484571
Morotti A, Arba F, Boulouis G, Charidimou A (2020) Noncontrast CT markers of intracerebral hemorrhage expansion and poor outcome: a meta-analysis. Neurology 95:632–643. https://doi.org/10.1212/WNL.0000000000010660
Zhong JW, Jin YJ, Song ZJ et al (2021) Deep learning for automatically predicting early haematoma expansion in Chinese patients. Stroke Vasc Neurol 6:610–614. https://doi.org/10.1136/svn-2020-000647
Katsuki M, Kakizawa Y, Nishikawa A, Yamamoto Y, Uchiyama T (2021) Postsurgical functional outcome prediction model using deep learning framework (Prediction One, Sony Network Communications Inc.) for hypertensive intracerebral hemorrhage. Surg Neurol Int 12:203. https://doi.org/10.25259/SNI_222_2021
Zhao X, Zhou B, Luo Y et al (2023) CT-based deep learning model for predicting hospital discharge outcome in spontaneous intracerebral hemorrhage. Eur Radiol. https://doi.org/10.1007/s00330-023-10505-610.1007/s00330-023-10505-6
Wang HL, Hsu WY, Lee MH et al (2019) Automatic machine-learning-based outcome prediction in patients with primary intracerebral hemorrhage. Front Neurol 10:910. https://doi.org/10.3389/fneur.2019.00910
Hemphill JC 3rd, Farrant M, Neill TA Jr (2009) Prospective validation of the ICH Score for 12-month functional outcome. Neurology 73:1088–1094. https://doi.org/10.1212/WNL.0b013e3181b8b332
Hall AN, Weaver B, Liotta E et al (2021) Identifying modifiable predictors of patient outcomes after intracerebral hemorrhage with machine learning. Neurocrit Care 34:73–84. https://doi.org/10.1007/s12028-020-00982-8