The Lancet

Detection of young-onset type 2 diabetes using deep learning across primary and secondary care: a nationwide, retrospective cohort study

aNovo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, ...
Northwestern's McCormick School of Engineering

Adaptive Algorithm Aims to Reduce Kidney Discards and Improve Transplant Access

Developed by Professor Sanjay Mehrotra, the Sliding Scale AdaptiVe Expedited (SAVE) algorithm could improve organ allocation ...

Industrial AI's Real Bottleneck Isn't the Algorithm

Walk through enough industrial AI deployments and a pattern becomes uncomfortable to ignore. The pilot works. The model ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
Phys.org

Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...
GitHub

Federated Learning under Distributed Concept Drift (FedDrift)

This repository is the source code for our paper: Federated Learning under Distributed Concept Drift (AISTATS'23). Federated Learning (FL) under distributed concept drift is a largely unexplored area.
IEEE

Construction of Visual Knowledge Graph Based on Distributed Machine Learning Algorithms

In today's digital age, visual data is experiencing explosive growth. Images, videos and other visual information contain rich semantic knowledge. However, due to their massive volume and complexity, ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Frontiers

A combined approach to lithology identification using reinforcement learning and transformer algorithms

Lithology identification plays a pivotal role in logging interpretation during drilling operations, directly influencing drilling decisions and efficiency. Conventional lithology identification ...