Deep learning in histopathology: the path to the clinic

J Van der Laak, G Litjens, F Ciompi - Nature medicine, 2021 - nature.com
Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …

Machine-learned potentials for next-generation matter simulations

P Friederich, F Häse, J Proppe, A Aspuru-Guzik - Nature Materials, 2021 - nature.com
The choice of simulation methods in computational materials science is driven by a
fundamental trade-off: bridging large time-and length-scales with highly accurate …

Compute trends across three eras of machine learning

J Sevilla, L Heim, A Ho, T Besiroglu… - … Joint Conference on …, 2022 - ieeexplore.ieee.org
Compute, data, and algorithmic advances are the three fundamental factors that drive
progress in modern Machine Learning (ML). In this paper we study trends in the most readily …

Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices

ATG Tapeh, MZ Naser - Archives of Computational Methods in …, 2023 - Springer
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …