Results 61 to 70 of about 1,295,192 (344)

Using Machine Learning and Candlestick Patterns to Predict the Outcomes of American Football Games

Applied Sciences, 2020
Match outcome prediction is a challenging problem that has led to the recent rise in machine learning being adopted and receiving significant interest from researchers in data science and sports. This study explores predictability in match outcomes using
Yu-Chia Hsu
doaj   +1 more source

Towards A Deeper Geometric, Analytic and Algorithmic Understanding of Margins

, 2015
Given a matrix $A$, a linear feasibility problem (of which linear classification is a special case) aims to find a solution to a primal problem $w: A^Tw > \textbf{0}$ or a certificate for the dual problem which is a probability distribution $p: Ap ...
Peña, Javier, Ramdas, Aaditya
core   +1 more source

Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema

BMC Ophthalmology, 2019
Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals.
Jin Mo Ahn, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho, Ungsoo S. Kim   +4 more
doaj   +1 more source

Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques [PDF]

SSRN Electronic Journal, 2019
The 2007-09 financial crisis revealed that the investors in the financial market were more concerned about the future as opposed to the current capital adequacies for banks. Stress testing promises to complement the regulatory capital adequacy regimes, which assess a bank’s current capital adequacy, with the ability to assess its future capital ...
Raymond Brummelhuis, Zhongmin Luo
openalex   +2 more sources

Statistical Mechanics of Soft Margin Classifiers

, 2001
We study the typical learning properties of the recently introduced Soft Margin Classifiers (SMCs), learning realizable and unrealizable tasks, with the tools of Statistical Mechanics.
A. Buhot, A. Buhot, B. Martos, C. Cortes, C. J. C. Burges, E. Gardner, G. Györgyi, G. Györgyi, H. S. Seung, J. Hertz, J.-I. Inoue, M. B. Gordon, M. Opper, M. Opper, M. Seeger, Mirta B. Gordon, O. Kinouchi, P. Peretto, P. Reimann, P. Sollich, R. Dietrich, R. Meir, S. Risau-Gusman, S. Risau-Gusman, S.-I. Amari, Sebastian Risau-Gusman, T. Cover, T. L. H. Watkin, T. Uezu, V. Vapnik, W. Krauth   +30 more
core   +1 more source

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

Molecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg, Joachim von Braun, Julio Celis, Anton Berns, Michael Baumann, Tit Albreht, Nancy Abou‐Zeid, Vanderlei Bagnato, Christian Brandts, Chien‐Jen Chen, Massimiliano di Pietro, Manjit Dosanjh, Thomas Dubois, Alexander Eggermont, Angelika Eggert, Ingemar Ernberg, Sara Faithfull, Johannes Förner, Stefan Fröhling, Manuel Heitor, Leroy Hood, Wei Jiang, Bengt Jönsson, Ravi Kannan, Maria Leptin, Su Li, Peter Lindgren, Douglas Lowy, Jun Ma, Alex Markham, Péter Nagy, Simon Oberst, M. Iqbal Parker, Danielle Rodin, Kevin Ryan, Joachim Schüz, Richard Sullivan, Josep Tabernero, Peter Turkson, Oliver Várhelyi, Harold Varmus, Chijie Wang, Elisabete Weiderpass, Nils Wilking   +43 more
wiley   +1 more source

Higher Amyloid and Tau Burden Is Associated With Faster Decline on a Digital Cognitive Test

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective A 2‐min digital clock‐drawing test (DCTclock) captures more granular features of the clock‐drawing process than the pencil‐and‐paper clock‐drawing test, revealing more subtle deficits at the preclinical stage of Alzheimer's disease (AD). A previous cross‐sectional study demonstrated that worse DCTclock performance was associated with
Jessie Fanglu Fu, Talia Robinson, Marina Rodriguez Alonso, Adela Francis Malave, Roos J. Jutten, Michael J. Properzi, Brian C. Healy, Jackson C. Thompson, Grace Del Carmen Montenegro, Emma Thibault, Dana Penney, Randall Davis, Reisa A. Sperling, Kathryn V. Papp, Keith A. Johnson, Julie C. Price, Dorene M. Rentz   +16 more
wiley   +1 more source

Portable Low‐Field Magnetic Resonance Imaging in People With Human Immunodeficiency Virus

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The aging population of people with HIV (PWH) raises heightened concerns regarding accelerated aging and dementia. Portable, low‐field MRI (LF‐MRI) is an innovative technology that could enhance access and facilitate routine monitoring of PWH.
Annabel Sorby‐Adams, Malachi Keo, Jennifer Guo, Daire Daly, Richard Ahern, Kimon Zachary, Gregory Robbins, Rajesh T. Gandhi, Bragi Sveinsson, Adam de Havenon, Kevin N. Sheth, Otto Rapalino, Juan Eugenio Iglesias Gonzales, W. Taylor Kimberly, Shibani S. Mukerji   +14 more
wiley   +1 more source

Hip Morphology–Based Osteoarthritis Risk Prediction Models: Development and External Validation Using Individual Participant Data From the World COACH Consortium

Arthritis Care &Research, EarlyView.
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg, Fleur Boel, Michiel M. A. van Buuren, Noortje S. Riedstra, Jinchi Tang, Harbeer Ahedi, Nigel K. Arden, Sita M. A. Bierma‐Zeinstra, Cindy G. Boer, Flavia M. Cicuttini, Timothy F. Cootes, David T. Felson, Willem Paul Gielis, Joshua Heerey, Graeme Jones, Stefan Kluzek, Nancy E. Lane, Claudia Lindner, Joyce B. J. van Meurs, Andrea Mosler, Amanda E. Nelson, Michael C. Nevitt, Edwin H. Oei, Jos Runhaar, Harrie Weinans, Jesse H. Krijthe, Rintje Agricola   +26 more
wiley   +1 more source

Karush-Kuhn-Tucker conditions and Lagrangian approach for improving machine learning techniques: A survey and new developments

Atti della Accademia Peloritana dei Pericolanti : Classe di Scienze Fisiche, Matematiche e Naturali
In this work we propose new proofs of some classical results of nonlinear programming milestones, in particular for the Kuhn-Tucker conditions and Lagrangian methods and functions.
Tiziana Ciano, Massimiliano Ferrara
doaj   +1 more source