Nature Search

Mapping global floods with 10 years of satellite radar data

Analysis of 10 years of satellite radar data with a deep learning model reveals historical flood patterns often missed in prior datasets. This dataset also enables analysis of trends in flooding, showing hints of increases in flood extent over time.

Amit Misra
Kevin White
Juan Lavista
ResearchOpen Access01 Jul 2025
Nature Communications

Volume: 16, P: 1-12
Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Seq2Symm is a sequence-based AI model designed to predict the symmetry of protein structures composed of identical chains, known as homo-oligomers. It surpasses existing methods in accuracy and efficiency, enabling rapid, proteome-scale predictions.

Meghana Kshirsagar
Artur Meller
Minkyung Baek
ResearchOpen Access27 Feb 2025
Nature Communications

Volume: 16, P: 1-11
Will AI accelerate or delay the race to net-zero emissions?

As artificial intelligence transforms the global economy, researchers need to explore scenarios to assess how it can help, rather than harm, the climate.

Amy Luers
Jonathan Koomey
Eric Horvitz
Comments & Opinion22 Apr 2024
Nature

Volume: 628, P: 718-720
Survey data and human computation for improved flu tracking

Digital trace data from search engines lacks information about the experiences of the individuals generating the data. Here the authors link search data and human computation to build a tracking model of influenza-like illness.

Stefan Wojcik
Avleen S. Bijral
David Lazer
ResearchOpen Access08 Jan 2021
Nature Communications

Volume: 12, P: 1-8
Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Cryptic pockets enable targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. Here, the authors develop a graph neural network that accurately predicts cryptic pockets in static structures by training using molecular simulation data alone.

Artur Meller
Michael Ward
Gregory R. Bowman
ResearchOpen Access01 Mar 2023
Nature Communications

Volume: 14, P: 1-15
Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19

Yixi Xu
Anusua Trivedi
Pavan K. Bhatraju
ResearchOpen Access08 Oct 2022
Scientific Reports

Volume: 12, P: 1-11
Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes

Anthony Ortiz
Anusua Trivedi
Juan M. Lavista Ferres
ResearchOpen Access02 Feb 2022
Scientific Reports

Volume: 12, P: 1-10
Multi-modal Language models in bioacoustics with zero-shot transfer: a case study

Zhongqi Miao
Benjamin Elizalde
Juan Lavista Ferres
ResearchOpen Access28 Feb 2025
Scientific Reports

Volume: 15, P: 1-12
Improved estimation of the relationship between fetal growth and late stillbirth in the United States, 2014–15

Darren Tanner
Juan M. Lavista Ferres
Edwin A. Mitchell
ResearchOpen Access12 Mar 2024
Scientific Reports

Volume: 14, P: 1-11
Evaluating the generalizability of deep learning image classification algorithms to detect middle ear disease using otoscopy

Al-Rahim Habib
Yixi Xu
Narinder Singh
ResearchOpen Access01 Apr 2023
Scientific Reports

Volume: 13, P: 1-9
Comparing recurrent convolutional neural networks for large scale bird species classification

Gaurav Gupta
Meghana Kshirsagar
Juan Lavista Ferres
ResearchOpen Access24 Aug 2021
Scientific Reports

Volume: 11, P: 1-12
The United States COVID-19 Forecast Hub dataset

Estee Y. Cramer
Yuxin Huang
Nicholas G. Reich
ResearchOpen Access01 Aug 2022
Scientific Data

Volume: 9, P: 1-15
An Artificial Intelligence Dataset for Solar Energy Locations in India

Anthony Ortiz
Dhaval Negandhi
Juan Lavista Ferres
ResearchOpen Access16 Aug 2022
Scientific Data

Volume: 9, P: 1-13

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