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most citedDeep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data

733 citations

Showing 2019Show all

8 papers · 1 filter

gr-qc2019★ 37 cited

The Classical Symmetron Force in Casimir Experiments

Benjamin Elder, Valeri Vardanyan, Yashar Akrami +3

The symmetron is a typical example of screened modified gravity, wherein the symmetron force is dynamically suppressed in dense environments. This allows it to hide in traditional…

math-ph2019★ 28 cited

-Plane Zeros of the Potts Partition Function on Diamond Hierarchical Graphs

Shu-Chiuan Chang, Roland K. W. Roeder, Robert Shrock

We report exact results concerning the zeros of the partition function of the Potts model in the complex plane, as a function of a temperature-like Boltzmann variable , for…

eess.IV2019★ 5 cited

Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images

David Joon Ho, Shuo Han, Chichen Fu +3

Fluorescence microscopy is an essential tool for the analysis of 3D subcellular structures in tissue. An important step in the characterization of tissue involves nuclei segmentati…

stat.ME2019★ 3 cited

Multimodal Neuroimaging Data Integration and Pathway Analysis

Yi Zhao, Lexin Li, Brian S. Caffo

With fast advancements in technologies, the collection of multiple types of measurements on a common set of subjects is becoming routine in science. Some notable examples include m…

physics.bio-ph2019★ 10 cited

Quantitative Kinetic Models from Intravital Microcopy: A Case Study Using Hepatic Transport

Meysam Tavakoli, Konstantinos Tsekouras, Richard Day +2

The liver performs critical physiological functions, including metabolizing and removing substances, such as toxins and drugs, from the bloodstream. Hepatotoxicity itself is intima…

eess.IV2019★ 733 cited

Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data

Taeho Jo, Kwangsik Nho, Andrew J. Saykin

Deep learning has shown outstanding performance in identifying intricate structures in complex high-dimensional data, especially in the domain of computer vision. The application o…

stat.ME2019★ 8 cited

Nonparametric tests for transition probabilities in nonhomogeneous Markov processes

Giorgos Bakoyannis

This paper proposes nonparametric two-sample tests for the direct comparison of the probabilities of a particular transition between states of a continuous time nonhomogeneous Mark…

math-ph2019★ 21 cited

Mixed moments of characteristic polynomials of random unitary matrices

Emma C. Bailey, Sandro Bettin, Gordon Blower +4

Following the work of Conrey, Rubinstein and Snaith and Forrester and Witte we examine a mixed moment of the characteristic polynomial and its derivative for matrices from the unit…