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.
New methods resolve conflicting treatment effect estimates in health tech assessments.
Meta-learning method for estimating time-varying mHealth intervention effects.
Automatically assesses the quality of online health articles.
Gaussian Process Regression improves damage assessment in structural health monitoring.
Study assesses health plan risk measures for Solvency Capital Requirement.
System recommends workouts and predicts success rates using RNNs.
Bayesian method for imputing actigraph data from mobile devices.
Italy and the Eurozone are heading in the year 2012 into a financial depression of unprecedented magnitude, with a forthcoming multitude of often contradictory public economic and financial stability emergency interventions whose ultimate endogenous and exogenous effects on public and private health spending and on the…
This paper explores crypto, blockchain, and Metaverse risks and opportunities.
The field of mobile health aims to leverage recent advances in wearable on-body sensing technology and smart phone computing capabilities to develop systems that can monitor health states and deliver just-in-time adaptive interventions. However, existing work has largely focused on analyzing collected data in the off-l…
New method assesses energy storage value beyond cost reduction.
The vision for precision medicine is to use individual patient characteristics to inform a personalized treatment plan that leads to the best healthcare possible for each patient. Mobile technologies have an important role to play in this vision as they offer a means to monitor a patient's health status in real-time an…
The paper develops methods for monitoring TPL machine health.
Automated model assesses online health info quality using machine learning.
Study improves data quality assessment for structural monitoring data.
Poultry farms are an important contributor to the human food chain. Worldwide, humankind keeps an enormous number of domesticated birds (e.g. chickens) for their eggs and their meat, providing rich sources of low-fat protein. However, around the world, there have been growing concerns about the quality of life for the …
Framework for responsible LLM deployment with human involvement and decentralized technologies.
Research in automatic affect recognition has seldom addressed the issue of computational resource utilization. With the advent of ambient intelligence technology which employs a variety of low-power, resource-constrained devices, this issue is increasingly gaining interest. This is especially the case in the context of…
This study seeks to validate a search protocol of ill health-related terms using Twitter data which can later be used to understand if, and how, Twitter can reveal information on the current health situation. We extracted conversations related to health and disease postings on Twitter using a set of pre-defined keyword…
Electronic health records are an increasingly important resource for understanding the interactions between patient health, environment, and clinical decisions. In this paper we report an empirical study of predictive modeling of several patient outcomes using three state-of-the-art machine learning methods. Our primar…
Study finds macroeconomic indicators predict health workforce and infrastructure measures.
PerSense assesses personality traits from text for commonsense reasoning.
AI improves precision health through adaptive interventions.
The paper analyzes tech specialization and diversification at various scales.
LHIEM model predicts health, income, and employment over years.
Paper assesses risks of stablecoins, from lending to business-to-business.
A lack of information exists about the health issues of lesbian, gay, bisexual, transgender, and queer (LGBTQ) people who are often excluded from national demographic assessments, health studies, and clinical trials. As a result, medical experts and researchers lack a holistic understanding of the health disparities fa…
National statistical systems are the enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposes - they allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, …
Deep learning predicts employment changes and industry health.
The treatment effects of medications play a key role in guiding medical prescriptions. They are usually assessed with randomized controlled trials (RCTs), which are expensive. Recently, large-scale electronic health records (EHRs) have become available, opening up new opportunities for more cost-effective assessments. …
Managing patients with chronic diseases is a major and growing healthcare challenge in several countries. A chronic condition, such as diabetes, is an illness that lasts a long time and does not go away, and often leads to the patient's health gradually getting worse. While recent works involve raw electronic health re…
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
There is an increasing interest in exploiting mobile sensing technologies and machine learning techniques for mental health monitoring and intervention. Researchers have effectively used contextual information, such as mobility, communication and mobile phone usage patterns for quantifying individuals' mood and wellbei…
Increasingly large electronic health records (EHRs) provide an opportunity to algorithmically learn medical knowledge. In one prominent example, a causal health knowledge graph could learn relationships between diseases and symptoms and then serve as a diagnostic tool to be refined with additional clinical input. Prior…
Proposes pT-Learning for optimal dynamic treatment regimes in mHealth.
Safety evaluation of self-driving technologies has been extensively studied. One recent approach uses Monte Carlo based evaluation to estimate the occurrence probabilities of safety-critical events as safety measures. These Monte Carlo samples are generated from stochastic input models constructed based on real-world d…
Structural variants compose the majority of human genetic variation, but are difficult to assess using current genomic sequencing technologies. Optical mapping technologies, which measure the size of chromosomal fragments between labeled markers, offer an alternative approach. As these technologies mature towards becom…
Paper develops methods for evaluating mHealth interventions using historical data.
SaML guides ML models to avoid survey biases.
Paper proposes ARPHMM for fault detection and prognosis in aero-engines.
Out of the companies, Dolby is the company with the best overall financial and operation health. According to the table that accounted its financial statements for the past three years, Dolby has stable profit margins that generates a revenue in the billions, the only company in ten figures. Corporate competition to ga…
With the expeditious advancement of information technologies, health-related data presented unprecedented potentials for medical and health discoveries but at the same time significant challenges for machine learning techniques both in terms of size and complexity. Those challenges include: the structured data with var…
Develops algorithms to balance personalization and statistical power in mobile health studies.
Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.
Paper explores physics-informed deep learning for system reliability assessment.
This paper analyzes air pollution trends in Rwanda using low-cost sensors and machine learning.
Patient journeys are compared to find clusters of similar disease trajectories.
VoxCeleb 2019 challenge assesses speaker recognition in uncontrolled settings.