Machin learning

artificial intelligence, robot, ai

Just fifty years ago, machine learning was still the stuff of science fiction. Today it’s an integral part of our lives, helping us do everything from finding photos to driving cars. We’ve come very far, very fast, thanks to countless philosophers, filmmakers, mathematicians, and computer scientists who fueled the dream of learning machines

Machine learning for medical diagnosis: history, state of the art and perspective

I Kononenko – Artificial Intelligence in medicine, 2001 – ElsevierThe paper provides an overview of the development of intelligent data analysis in medicine
from a machine learning perspective: a historical view, a state-of-the-art view, and a view on
some future trends in this subfield of applied artificial intelligence. The paper is not intended …Cited by 1189Related articlesAll 10 versions[HTML]

[HTML] Frontotemporal correlates of impulsivity and machine learning in retired professional athletes with a history of multiple concussions

R Goswami, P Dufort, MC Tartaglia, RE Green… – Brain structure and …, 2016 – SpringerThe frontotemporal cortical network is associated with behaviours such as impulsivity and
aggression. The health of the uncinate fasciculus (UF) that connects the orbitofrontal cortex
(OFC) with the anterior temporal lobe (ATL) may be a crucial determinant of behavioural …Cited by 76Related articlesAll 16 versions[PDF]

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: A machine learning study

S KinreichJL Meyers, A Maron-Katz… – Molecular …, 2019 – nature.comPredictive models have succeeded in distinguishing between individuals with Alcohol use
Disorder (AUD) and controls. However, predictive models identifying who is prone to
develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our …Cited by 5Related articlesAll 9 versions[PDF]

Using machine learning to translate applicant work history into predictors of performance and turnover.

S SajjadianiAJ Sojourner… – Journal of Applied …, 2019 – psycnet.apa.orgWork history information reflected in resumes and job application forms is commonly used to
screen job applicants; however, there is little consensus as to how to systematically translate
information about one’s work-related past into predictors of future work outcomes. In this …Cited by 12Related articlesAll 8 versions

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Spatial strain correlations, machine learning, and deformation history in crystal plasticity

S Papanikolaou, M Tzimas, ACE Reid, SA Langer – Physical Review E, 2019 – APSAbstract Systems far from equilibrium respond to probes in a history-dependent manner. The
prediction of the system response depends on either knowing the details of that history or
being able to characterize all the current system properties. In crystal plasticity, various …Cited by 8Related articlesAll 6 versions[PDF] iop.orgFull View

Machine Learning Applied to the Reionization History of the Universe in the 21 cm Signal

P La Plante, M Ntampaka – The Astrophysical Journal, 2019 – iopscience.iop.orgAbstract The Epoch of Reionization (EoR) features a rich interplay between the first
luminous sources and the low-density gas of the intergalactic medium (IGM), where photons
from these sources ionize the IGM. There are currently few observational constraints on key …Cited by 8Related articlesAll 3 versions

machine learning algorithm for analyzing string patterns helps to discover simple and interpretable business rules from purchase history

Y Hamuro, H Kawata, N Katoh, K Yada – Progress in Discovery Science, 2002 – SpringerThis paper presents a new application for discovering useful knowledge from purchase
history that can be helpful to create effective marketing strategy, using a machine learning
algorithm, BONSAI, proposed by Shimozono et al. in 1994 which was originally developed …Cited by 29Related articlesAll 10 versions

Machine learning model to predict recurrent ulcer bleeding in patients with history of idiopathic gastroduodenal ulcer bleeding

GLH WongAJ MaH Deng, JYL Ching… – Alimentary …, 2019 – Wiley Online LibraryBackground Patients with a history of Helicobacter pylori–negative idiopathic bleeding
ulcers have an increased risk of recurring ulcer complications. Aim To build a machine
learning model to identify patients at high risk for recurrent ulcer bleeding. Methods Data …Cited by 11Related articlesAll 4 versions[PDF]

[PDF] Machine Learning-Based Malware Detection for Android Applications: History Matters!

K AllixTFDA BissyandeJ KleinY Le Traon – 2014 – Machine Learning-based malware detection is a promising scalable method for
identifying suspicious applications. In particular, in today’s mobile computing realm where
thousands of applications are daily poured into markets, such a technique could be valuable …Cited by 20Related articlesAll 2 versions

Fetal health status prediction based on maternal clinical history using machine learning techniques

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