A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study of red blood cells using elastic surface theory.
Mathematical model describes how red blood cells return to equilibrium.
New method classifies reticulocytes from red blood cells without labels.
Malaria is a female anopheles mosquito-bite inflicted life-threatening disease which is considered endemic in many parts of the world. This article focuses on improving malaria detection from patches segmented from microscopic images of red blood cell smears by introducing a deep convolutional neural network. Compared …
Cell detection and cell type classification from biomedical images play an important role for high-throughput imaging and various clinical application. While classification of single cell sample can be performed with standard computer vision and machine learning methods, analysis of multi-label samples (region containi…
DISPR uses diffusion models to predict 3D cell shapes from 2D images.
This study automates blood cell classification using computer vision.
CST-YOLO improves blood cell detection with YOLOv7 and CNN-Swin Transformer.
Novel framework for whole-slide blood cell segmentation.
TIMELY improves consistency in labeling blood cell images.
Counting and classifying blood cells is an important diagnostic tool in medicine. Support Vector Machines are increasingly popular and efficient and could replace artificial neural network systems. Here a method to classify blood cells is proposed using SVM. A set of statistics on images are implemented in C++. The MPE…
In this paper, we are interested in shape optimization problems involving the ge ometry (normal, curvatures) of the surfaces. We consider a class of hypersurface s in satisfying a uniform ball condition and we prove the exist ence of a -regular minimizer for general geometric functionals and c…
The Helfrich functional, denoted by H^{c_0}, is a mathematical expression proposed by Helfrich (1973) for the natural free energy carried by an elastic phospholipid bilayer. Helfrich theorises that idealised elastic phospholipid bilayers minimise H^{c_0} among all possible configurations. The functional integrates a sp…
DCENWCNet improves WBC classification with LIME-based explainability.
A low-cost, robust, and simple mechanism to measure hemoglobin would play a critical role in the modern health infrastructure. Consistent sample acquisition has been a long-standing technical hurdle for photometer-based portable hemoglobin detectors which rely on micro cuvettes and dry chemistry. Any particulates (e.g.…
We present a Bayesian hierarchical multi-view mixture model termed Symphony that simultaneously learns clusters of cells representing cell types and their underlying gene regulatory networks by integrating data from two views: single-cell gene expression data and paired epigenetic data, which is informative of gene-gen…
We preset a computational study of bending models for the curvature elasticity of lipid bilayer membranes that are relevant for simulations of vesicles and red blood cells. We compute bending energy and forces on triangulated meshes and evaluate and extend four well established schemes for their approximation: Kantor a…
The study compares different scRNA sequencing methods using a high-dimensional dataset.
Detecting aggressive cancer tumors using ctDNA dynamics from few blood samples.
scICML integrates multi-omics data from single cells using co-clustering.
Using the mechanics of creep in material sciences as a metaphor, we present a general framework to understand the evolution of financial, economic and social systems and to construct scenarios for the future. In a nutshell, highly non-linear out-of-equilibrium systems subjected to exogenous perturbations tend to exhibi…
Many scientific questions require estimating the effects of continuous treatments. Outcome modeling and weighted regression based on the generalized propensity score are the most commonly used methods to evaluate continuous effects. However, these techniques may be sensitive to model misspecification, extreme weights o…
Hydroxyurea (HU) has been shown to be effective in alleviating the symptoms of Sickle Cell Anemia disease. While Hydroxyurea reduces the complications associated with Sickle Cell Anemia in some patients, others do not benefit from this drug and experience deleterious effects since it is also a chemotherapeutic agent. T…
Graph Attention Networks predict disease state from single-cell data.
Tree-SNE combines t-SNE and hierarchical clustering for data visualization.
Flow cytometry is a high-throughput technology used to quantify multiple surface and intracellular markers at the level of a single cell. This enables to identify cell sub-types, and to determine their relative proportions. Improvements of this technology allow to describe millions of individual cells from a blood samp…
This paper presents the recurrent estimation of distributions (RED) for modeling real-valued data in a semiparametric fashion. RED models make two novel uses of recurrent neural networks (RNNs) for density estimation of general real-valued data. First, RNNs are used to transform input covariates into a latent space to …
ReD improves LLM inference efficiency at fixed budget, reducing attempts and cost.
Blood glucose value prediction is an important task in diabetes management. While it is reported that glucose concentration is sensitive to social context such as mood, physical activity, stress, diet, alongside the influence of diabetes pathologies, we need more research on data and methodologies to incorporate and ev…
Generative ML learns optimal pursuit trajectories in pursuit-evasion games.
RED CoMETS improves multivariate time series classification accuracy.
Unified framework for semi-supervised learning reduces annotation needs.
SPT predicts age and mass of red giants from spectra.
Machine learning model diagnoses COVID-19 from routine blood tests.
Quantization and reduction for coisotropic A-branes on Hamiltonian manifolds.
This study uses deep learning to infer stellar parameters from short TESS and K2 observations.
Proposes RPG-RT for red-teaming T2I models without internal access.
Develops a tool to identify abnormal blood smear results based on CBC tests.
A deep learning network was used to predict future blood glucose levels, as this can permit diabetes patients to take action before imminent hyperglycaemia and hypoglycaemia. A sequential model with one long-short-term memory (LSTM) layer, one bidirectional LSTM layer and several fully connected layers was used to pred…
New framework assesses LLM security risks in BFSI.
In this paper, we introduce an insurance ruin model with adaptive premium rate, thereafter refered to as restructuring/refraction, in which classical ruin and bankruptcy are distinguished. In this model, the premium rate is increased as soon as the wealth process falls into the red zone and is brought back to its regul…
New method estimates effects of multiple nutrients on blood glucose.
Study discovers patterns in insulin needs for T1D patients.
We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen) more accurately than trained anesthesiologists with access to all the data recorded in a modern operating room. We also provide a simple way…
RED-2400 is a public benchmark of trading events from a Solana exchange, labeled by algorithmic rejection.
Deep RL improves blood glucose control for T1D patients.
Computational Drug Repositioning (CDR) is the task of discovering potential new indications for existing drugs by mining large-scale heterogeneous drug-related data sources. Leveraging the patient-level temporal ordering information between numeric physiological measurements and various drug prescriptions provided in E…
AI tool automates blood segmentation from head CT scans after SAH.