Results 41 to 50 of about 1,737,261 (319)

An imbalance-aware deep neural network for early prediction of preeclampsia.

PLoS ONE, 2022
Preeclampsia (PE) is a hypertensive complication affecting 8-10% of US pregnancies annually. While there is no cure for PE, aspirin may reduce complications for those at high risk for PE. Furthermore, PE disproportionately affects racial minorities, with
Rachel Bennett, Zuber D Mulla, Pavan Parikh, Alisse Hauspurg, Talayeh Razzaghi   +4 more
doaj   +1 more source

Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks

Sensors, 2022
Arrhythmia detection algorithms based on deep learning are attracting considerable interest due to their vital role in the diagnosis of cardiac abnormalities.
Muhammad Zubair, Changwoo Yoon
doaj   +1 more source

Schaefer's theorem for graphs [PDF]

, 2015
Schaefer's theorem is a complexity classification result for so-called Boolean constraint satisfaction problems: it states that every Boolean constraint satisfaction problem is either contained in one out of six classes and can be solved in polynomial ...
Bodirsky, Manuel, Pinsker, Michael
core   +2 more sources

On the connection between quantum nonlocality and phase sensitivity of two-mode entangled Fock state superpositions [PDF]

, 2015
In two-mode interferometry, for a given total photon number $N$, entangled Fock state superpositions of the form $(|N-m\rangle_a|m\rangle_b+e^{i (N-2m)\phi}|m\rangle_a|N-m\rangle_b)/\sqrt{2}$ have been considered for phase estimation.
Dowling, Jonathan P., Kim, Moochan B., Lee, Hwang, Seshadreesan, Kaushik P., Wildfeuer, Christoph   +4 more
core   +3 more sources

Unconventional machine learning of genome-wide human cancer data

, 2020
Recent advances in high-throughput genomic technologies coupled with exponential increases in computer processing and memory have allowed us to interrogate the complex aberrant molecular underpinnings of human disease from a genome-wide perspective ...
Bajaj, Sweta R., Chittenden, Thomas W., Cilfone, Nicholas, Gamel, Omar E., Gujja, Sharvari, Gulcher, Jeffrey R., Li, Richard Y., Lidar, Daniel A.   +7 more
core   +1 more source

ROC Curves, Loss Functions, and Distorted Probabilities in Binary Classification

Mathematics, 2022
The main purpose of this work is to study how loss functions in machine learning influence the “binary machines”, i.e., probabilistic AI models for predicting binary classification problems.
Phuong Bich Le, Zung Tien Nguyen
doaj   +1 more source

Bayesian estimation of the Pareto model based on type-II censoring data by employing non-linear programming

Alexandria Engineering Journal
The main goal of this article is to determine the optimally weighted coefficients (Ω1and Ω2) of the balanced loss function of the form. LΚ,Ω,ξoΨ(σ),ξ=Ω1γσΚξo,ξ+Ω2γσΚΨ(σ),ξ;Ω1+Ω2=1.
Laila A. AL-Essa, Fuad S. Al-Duais, Walid Aydi, Afrah Y. AL-Rezami   +3 more
doaj   +1 more source

Machine Learning Techniques for Stellar Light Curve Classification [PDF]

, 2018
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical properties ...
Hinners, Trisha, Tat, Kevin, Thorp, Rachel   +2 more
core   +2 more sources

Time-dependent modeling of pulsar wind nebulae: Study on the impact of the diffusion-loss approximations

, 2012
In this work, we present a leptonic, time-dependent model of pulsar wind nebulae (PWNe). The model seeks a solution for the lepton distribution function considering the full time-energy dependent diffusion-loss equation.
Abdo, Actis, Aharonian, Aharonian, Aharonian, Albert, Atoyan, Atoyan, Baldwin, Bednarek, Bednarek, Blumenthal, Bucciantini, Büsching, de Jager, de Oña, Diego F. Torres, Fang, Gaensler, Gelfand, Ginzburg, Ginzburg, Grasdalen, Green, Grondin, Haug, Hennessy, Holler, Jonatan Martín, Kargaltsev, Kennel, Kuiper, Lewin, Li, Lyne, Macías-Pérez, Manchester, Marsden, Nanda Rea, Ney, Qiao, Rea, Rees, Schlickeiser, Smith, Spitkovsky, Tanaka, Tanaka, Taylor, Temim, van der Swaluw, Van Etten, Vinyaikin, Volpi, Véron-Cetty, Zhang   +55 more
core   +1 more source

PT-Symmetric Nonlinear Metamaterials and Zero-Dimensional Systems

, 2013
A one dimensional, parity-time (${\cal PT}$)-symmetric magnetic metamaterial comprising split-ring resonators having both gain and loss is investigated.
Lazarides, N., Tsironis, G. P.
core   +1 more source