DeepSurv
DeepSurv ni mbinu ya mtandao wa neva wa kina kwa uchambuzi wa uhai inayojifunza usambazaji wa uhai uliobinafsishwa moja kwa moja kutoka kwa data. Iliyotambulishwa na Katzman et al. mwaka 2018, inapanua mfumo wa hatari sawia wa Cox kwa kutumia ujifunzaji wa kina ili kunasa uhusiano changamano, usio wa mstari kati ya vigezo tegemezi na matokeo ya uhai. Inasuluhisha tatizo la kuiga athari za matibabu zisizo sawa na utabiri wa muda wa tukio katika mipangilio yenye vipimo vingi.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- Faraggi, D., & Simon, R. (1995). A neural network model for survival data. Statistics in Medicine, 14(1), 73–82. DOI: 10.1002/sim.4780140108 ↗
- Katzman, J. L., et al. (2018). DeepSurv: Personalized treatment recommender system using a Cox proportional hazards deep neural network. Journal of Machine Learning Research, 40, 40–51. DOI: 10.1186/s12874-018-0482-1 ↗
- Lee, C., Zame, W., Yoon, J., & van der Schaar, M. (2018). Deephit: A deep learning approach for dynamic survival analysis. AAAI Conference on Artificial Intelligence, 32(1). link ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Deep Learning for Survival Analysis. ScholarGate. https://scholargate.app/sw/survival/deepsurv
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Mfumo wa Kuongeza kasi ya Kushindwa kwa Wakati (AFT)Uchanganuzi wa Uhai↔ compare
- Rega ya Hatari za Uwiano wa CoxUchanganuzi wa Uhai↔ compare
- Regressioni ya Kuishi ya Weibull ya ParametricUchanganuzi wa Uhai↔ compare
Imerejelewa na
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