Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting

Autor: David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Lió

Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-18 (2024)

Abstract We investigate the potential of graph neural networks for transfer learning and improving molecular property prediction on sparse and expensive to acquire high-fidelity data by leveraging low-fidelity measurements as an inexpensive proxy for

Externí odkaz: https://doaj.org/article/251a42072929455bae64c461d4f81cc6

Modelling local and general quantum mechanical properties with attention-based pooling

Autor: David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò

Publikováno v: Communications Chemistry, Vol 6, Iss 1, Pp 1-11 (2023)

Abstract Atom-centred neural networks represent the state-of-the-art for approximating the quantum chemical properties of molecules, such as internal energies. While the design of machine learning architectures that respect chemical principles has co

Externí odkaz: https://doaj.org/article/0408d9d75f634d17829a190fbf257f59

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

Evaluating clinical outcomes and prognosis in patients with cirrhosis and portal hypertension: a retrospective observational cohort study

Autor: Daniel M Bean, Peter J Greasley, Philip Ambery, Phillip R Hunt, Nerissa Hoi Ching Lee, Steven J Kiddle, Shardul Chandankhede, Shubh Agrawal, Victoria E R Parker

Publikováno v: BMJ Open Gastroenterology, Vol 10, Iss 1 (2023)

Objective Cirrhosis describes the end-stage of chronic liver disease. Irreversible changes in the liver cause portal hypertension, which can progress to serious complications and death. Only a few studies with small sample sizes have investigated the

Externí odkaz: https://doaj.org/article/3f6b62f582ac49219c5a5c61e6207f6d

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