Results 51 to 60 of about 1,147,666 (317)

PREDICTIVE ANALYSIS OF HEART DISEASES WITH MACHINE LEARNING APPROACHES

Malaysian Journal of Computer Science, 2022
Machine Learning (ML) is used in healthcare sectors worldwide. ML methods help in the protection of heart diseases, locomotor disorders in the medical data set.
Ramesh Tr, U. Lilhore, P. M., Sarita Simaiya, Amandeep Kaur, Mounir Hamdi   +5 more
semanticscholar   +1 more source

Applying a Random Projection Algorithm to Optimize Machine Learning Model for Breast Lesion Classification [PDF]

IEEE Transactions on Biomedical Engineering, 2020
Objective: Since computer-aided diagnosis (CAD) schemes of medical images usually computes large number of image features, which creates a challenge of how to identify a small and optimal feature vector to build robust machine learning models, the ...
Morteza Heidari, S. Lakshmivarahan, Seyedehnafiseh Mirniaharikandehei, Gopichandh Danala, S. K. Maryada, Hong Liu, B. Zheng, School of Electrical, Computer Engineering, U. Oklahoma, Norman, Ok, Usa, School of Computer Sciences   +13 more
semanticscholar   +1 more source

Machine learning and artificial neural network accelerated computational discoveries in materials science [PDF]

WIREs Computational Molecular Science, 2019
AbstractArtificial intelligence (AI) has been referred to as the “fourth paradigm of science,” and as part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically accelerates the computational discoveries. As the machinery for ML algorithms matures, significant advances have been made not only by the mainstream AI ...
Yang Hong, Bo Hou, Hengle Jiang, Jingchao Zhang   +3 more
openaire   +2 more sources

Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case [PDF]

, 2018
Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new ...
A. J. Connolly, AA Collister, Abdalla, B Hoyle, C. Laigle, CA Blake, CP Ahn, D Wittman, Daniel Masters, David W. Gerdes, H Hildebrandt, I Sadeh, JTA Jong de, K Carrasco, K Carrasco, M Annunziatella, M Bolzonella, M Brescia, M Brescia, M Brescia, Masayuki Tanaka, N Benitez, O Ilbert, O Laurino, P Dubath, S Arnouts, S Cavuoti, S Cavuoti, S Cavuoti, S Cavuoti, S Cavuoti, S Cavuoti, S Cavuoti, T Gneiting   +33 more
core   +2 more sources

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

Artificial Intelligence for the Earth Systems, 2023
Climate variability and weather phenomena can cause extremes and pose significant risk to society and ecosystems, making continued advances in our physical understanding of such events of utmost importance for regional and global security.
M. Molina, T. O’Brien, G. Anderson, M. Ashfaq, K. Bennett, W. Collins, K. Dagon, J. Restrepo, P. Ullrich   +8 more
semanticscholar   +1 more source

Machine Learning Bell Nonlocality in Quantum Many-body Systems

, 2017
Machine learning, the core of artificial intelligence and big data science, is one of today's most rapidly growing interdisciplinary fields. Recently, its tools and techniques have been adopted to tackle intricate quantum many-body problems. In this work,
Deng, Dong-Ling
core   +1 more source

A Review on Background and Applications of Machine Learning in Materials Research

Journal of Computational Intelligence in Materials Science, 2023
In recent decades, Artificial Intelligence (AI) has garnered considerable interest owing to its potential to facilitate greater levels of automation and speed up overall output. There has been a significant increase in the quantity of training data sets,
Robert Ahmed, Christna Ahler
semanticscholar   +1 more source

Climbing down Charney’s ladder: machine learning and the post-Dennard era of computational climate science [PDF]

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021
The advent of digital computing in the 1950s sparked a revolution in the science of weather and climate. Meteorology, long based on extrapolating patterns in space and time, gave way to computational methods in a decade of advances in numerical weather forecasting.
openaire   +4 more sources

REFORMS: Consensus-based Recommendations for Machine-learning-based Science

Science Advances
Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and generalizability.
Sayash Kapoor, Emily M Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A Bail, Odd Erik Gundersen, Jake M. Hofman, J. Hullman, M. Lones, M. Malik, Priyanka Nanayakkara, R. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan   +18 more
semanticscholar   +1 more source

A review of molecular representation in the age of machine learning

WIREs Computational Molecular Science, 2022
Research in chemistry increasingly requires interdisciplinary work prompted by, among other things, advances in computing, machine learning, and artificial intelligence.
Daniel S. Wigh, J. Goodman, A. Lapkin
semanticscholar   +1 more source