Deep learning for comprehensive forecasting of Alzheimer's Disease progression

10 July 2018

Papers citing "Deep learning for comprehensive forecasting of Alzheimer's Disease progression"

5 / 5 papers shown

Title
REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers Aivin V. Solatorio Olivier Dupriez LMTD 26 62 0 04 Feb 2023
TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography Tengfei Xue Fan Zhang L. Zekelman Chaoyi Zhang Yuqian Chen ... W. Wells Yogesh Rathi N. Makris Weidong Cai L. O’Donnell 38 7 0 13 Oct 2022
Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review Sayantan Kumar I. Oh S. Schindler A. Lai Philip R. O. Payne Aditi Gupta 68 73 0 05 Aug 2021
Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score Alejandro Schuler D. Walsh D.F. Hall J. Walsh Charles K. Fisher 20 32 0 17 Dec 2020
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 36 17 0 27 May 2020