Dynamic Factor Analysis with Dependent Gaussian Processes for High-Dimensional Gene Expression Trajectories

Autor: Cai, Jiachen, Goudie, Robert J. B., Starr, Colin, Tom, Brian D. M.

The increasing availability of high-dimensional, longitudinal measures of gene expression can facilitate understanding of biological mechanisms, as required for precision medicine. Biological knowledge suggests that it may be best to describe complex

Externí odkaz: http://arxiv.org/abs/2307.02781

Sequential Re-estimation Learning of Optimal Individualized Treatment Rules Among Ordinal Treatments with Application to Recommended Intervals Between Blood Donations

Autor: Xu, Yuejia, Wood, Angela M., Roberts, David J., Tom, Brian D. M.

Personalized medicine has gained much popularity recently as a way of providing better healthcare by tailoring treatments to suit individuals. Our research, motivated by the UK INTERVAL blood donation trial, focuses on estimating the optimal individu

Externí odkaz: http://arxiv.org/abs/2302.11638

Trends in risks of severe events and lengths of stay for COVID-19 hospitalisations in England over the pre-vaccination era: results from the Public Health England SARI-Watch surveillance scheme

Autor: Kirwan, Peter D., Elgohari, Suzanne, Jackson, Christopher H., Tom, Brian D. M., Mandal, Sema, De Angelis, Daniela, Presanis, Anne M.

Background: Trends in hospitalised case-fatality risk (HFR), risk of intensive care unit (ICU) admission and lengths of stay for patients hospitalised for COVID-19 in England over the pre-vaccination era are unknown. Methods: Data on hospital and ICU

Externí odkaz: http://arxiv.org/abs/2103.04867

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

Autor: Marinescu, Razvan V., Oxtoby, Neil P., Young, Alexandra L., Bron, Esther E., Toga, Arthur W., Weiner, Michael W., Barkhof, Frederik, Fox, Nick C., Eshaghi, Arman, Toni, Tina, Salaterski, Marcin, Lunina, Veronika, Ansart, Manon, Durrleman, Stanley, Lu, Pascal, Iddi, Samuel, Li, Dan, Thompson, Wesley K., Donohue, Michael C., Nahon, Aviv, Levy, Yarden, Halbersberg, Dan, Cohen, Mariya, Liao, Huiling, Li, Tengfei, Yu, Kaixian, Zhu, Hongtu, Tamez-Pena, Jose G., Ismail, Aya, Wood, Timothy, Bravo, Hector Corrada, Nguyen, Minh, Sun, Nanbo, Feng, Jiashi, Yeo, B. T. Thomas, Chen, Gang, Qi, Ke, Chen, Shiyang, Qiu, Deqiang, Buciuman, Ionut, Kelner, Alex, Pop, Raluca, Rimocea, Denisa, Ghazi, Mostafa M., Nielsen, Mads, Ourselin, Sebastien, Sorensen, Lauge, Venkatraghavan, Vikram, Liu, Keli, Rabe, Christina, Manser, Paul, Hill, Steven M., Howlett, James, Huang, Zhiyue, Kiddle, Steven, Mukherjee, Sach, Rouanet, Anais, Taschler, Bernd, Tom, Brian D. M., White, Simon R., Faux, Noel, Sedai, Suman, Oriol, Javier de Velasco, Clemente, Edgar E. V., Estrada, Karol, Aksman, Leon, Altmann, Andre, Stonnington, Cynthia M., Wang, Yalin, Wu, Jianfeng, Devadas, Vivek, Fourrier, Clementine, Raket, Lars Lau, Sotiras, Aristeidis, Erus, Guray, Doshi, Jimit, Davatzikos, Christos, Vogel, Jacob, Doyle, Andrew, Tam, Angela, Diaz-Papkovich, Alex, Jammeh, Emmanuel, Koval, Igor, Moore, Paul, Lyons, Terry J., Gallacher, John, Tohka, Jussi, Ciszek, Robert, Jedynak, Bruno, Pandya, Kruti, Bilgel, Murat, Engels, William, Cole, Joseph, Golland, Polina, Klein, Stefan, Alexander, Daniel C.

Publikováno v: Machine Learning for Biomedical Imaging (MELBA), Dec 2021

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk

Externí odkaz: http://arxiv.org/abs/2002.03419

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.