arXiv research

Deep learning for integrating diverse clinical measurements.

Extends nonlinear filtering to predictable jump times.

Framework for estimating treatment effects using external control data.

We link disjoint longitudinal data for rare disease patients using latent representations and mixed-effects regression.

Statistical approach uses ODEs for modeling individual health trajectories.

New algorithm extracts shared latent space for cortico-muscular interactions.

This paper critiques the Standardized Measurement Approach (SMA) for operational risk and recommends maintaining Advanced Measurement Approach (AMA).

On March 4th 2016 the Basel Committee on Banking Supervision published a consultative document where a new methodology, called the Standardized Measurement Approach (SMA), is introduced for computing Operational Risk regulatory capital for banks. In this note, the behavior of the SMA is studied under a variety of hypot…

Deep learning models brain deformations based on atrophy and growth data.

Spinal cord stimulation has enabled humans with motor complete spinal cord injury (SCI) to independently stand and recover some lost autonomic function. Quantifying the quality of bipedal standing under spinal stimulation is important for spinal rehabilitation therapies and for new strategies that seek to combine spina…

Quantifying the degree of atrophy is done clinically by neuroradiologists following established visual rating scales. For these assessments to be reliable the rater requires substantial training and experience, and even then the rating agreement between two radiologists is not perfect. We have developed a model we call…

New tools classify symplectic fillings of contact 3-manifolds.

Recently, Basel Committee for Banking Supervision proposed to replace all approaches, including Advanced Measurement Approach (AMA), for operational risk capital with a simple formula referred to as the Standardised Measurement Approach (SMA). This paper discusses and studies the weaknesses and pitfalls of SMA such as …

In Heisenberg group, bisectors are spinal spheres with specific curvature.

A spinal open book decomposition on a contact manifold is a generalization of a supporting open book which exists naturally e.g. on the boundary of a symplectic filling with a Lefschetz fibration over any compact oriented surface with boundary. In this first paper of a two-part series, we introduce the basic notions re…

This paper classifies symplectic and Stein fillings of contact 3-manifolds with spinal open book decompositions.

The diagnosis of Alzheimer's disease (AD) in routine clinical practice is most commonly based on subjective clinical interpretations. Quantitative electroencephalography (QEEG) measures have been shown to reflect neurodegenerative processes in AD and might qualify as affordable and thereby widely available markers to f…

Deep learning segments spinal metastases in MR images.

New contact manifolds with many fillings found.

The development of machine learning systems for the diagnosis of rare diseases is challenging mainly due the lack of data to study them. Despite this challenge, this paper proposes a system for the Computer Aided Diagnosis (CAD) of low-prevalence, congenital muscular dystrophies from confocal microscopy images. The pro…

The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see t…

We study the finitely generated Hausdorff spectrum of spinal automorphism groups acting on rooted trees. Given any $α\in [0,1]$, we construct a branch group $G_α$ such that $G_α$ has a finitely generated subgroup $H$ where $H$ has Hausdorff dimension $α$ in $G$. Using results by Barnea, Shalev and Klopsch we further de…

Study proposes deep learning techniques to diagnose and differentiate Celiac Disease and Environmental Enteropathy from biopsy images.

Male infertility is a disease which affects approximately 7% of men. Sperm morphology analysis (SMA) is one of the main diagnosis methods for this problem. Manual SMA is an inexact, subjective, non-reproducible, and hard to teach process. As a result, in this paper, we introduce a novel automatic SMA based on a neural …

MAGIC uncovers disease heterogeneity across brain scales.

ML predicts alloy properties considering chemistry, processing, and data transformations.

We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated observations of subjects at different time points which take the form of measurement maps distributed on a graph such as an image or a mesh. Th…

We prove that for any contact 3-manifold supported by a spinal open book decomposition with planar pages, there is a universal bound on the Euler characteristic and signature of its minimal symplectic fillings. The proof is an application of the spine removal surgery operation recently introduced in joint work of the a…

We prove that if a contact manifold $(M,ξ)$ is supported by a planar open book, then Euler characteristic and signature of any Stein filling of $(M,ξ)$ is bounded. We also prove a similar finiteness result for contact manifolds supported by spinal open books with planar pages. Moving beyond the geography of Stein filli…

This paper describes a new neuroimaging analysis toolbox that allows for the modeling of nonlinear effects at the voxel level, overcoming limitations of methods based on linear models like the GLM. We illustrate its features using a relevant example in which distinct nonlinear trajectories of Alzheimer's disease relate…

We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even when only limited, unimodal data is available, by transferring information from …

We study the way a strongly irreducible Heegaard surface $Σ$ intersects a knot exterior $X$ embedded in a 3-manifold, and show that if $Σ\cap \partial X$ consists of simple closed curves which are essential in both $Σ$ and $\partial X$, then the intersection $X \cap Σ$ consists of meridional annuli only. As an applicat…

We show that there are vast families of contact 3-manifolds each member of which admits infinitely many Stein fillings with arbitrarily big euler characteristics and arbitrarily small signatures ---which disproves a conjecture of Stipsicz and Ozbagci. To produce our examples, we set a framework which generalizes the co…

Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from short-term longitudinal data sets. DIVE clusters vertex-wise biomarker measurements on the cortical surf…

Smile-GANs clusters brain MRI scans to reveal disease subtypes and progression.

EXAGREE selects a stakeholder-aligned model to reduce conflicting explanations in machine learning.

Automatically counts microglial cells in rat spinal cord images, providing precise counts and uncertainty estimates.

Fast, accurate thalamus segmentation method for MS and ET.

Novel approach combines local and global brain changes for AD prediction.

Early prognosis of Alzheimer's dementia is hard. Mild cognitive impairment (MCI) typically precedes Alzheimer's dementia, yet only a fraction of MCI individuals will progress to dementia, even when screened using biomarkers. We propose here to identify a subset of individuals who share a common brain signature highly p…

This paper optimizes cryptocurrency portfolios by integrating sentiment analysis with technical indicators.

Planar multilinks prove rational singularities in surface geometry.

The paper presents algorithms for diagnosing Pathological Myopia and detecting retinal structures.

Glioma is one of the most common types of brain tumors; it arises in the glial cells in the human brain and in the spinal cord. In addition to having a high mortality rate, glioma treatment is also very expensive. Hence, automatic and accurate segmentation and measurement from the early stages are critical in order to …

Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities. Among the existing solutions the systems relying on electroencephalograms (EEG) occupy the most prominent place due to their non-invasiveness. However, t…

How effective are the most common trading models? The answer may help investors realize upsides to using each model, act as a segue for investors into more complex financial analysis and machine learning, and to increase financial literacy amongst students. Creating original versions of popular models, like linear regr…

Enforcing safety is a key aspect of many problems pertaining to sequential decision making under uncertainty, which require the decisions made at every step to be both informative of the optimal decision and also safe. For example, we value both efficacy and comfort in medical therapy, and efficiency and safety in robo…

Develops a universal Hermitian projective calculus for complex hyperbolic two-space