leveraging comprehensive baseline datasets to

Leveraging electronic health records data to predict

Leveraging electronic health records data to predict multiple sclerosis disease activity. Sign in The performance was significantly better than the baseline model (age, , race/ethnicity, and disease duration) and noninferior to a model containing actual prior 1

Who

The 'Who' impact dimension refers to the stakeholders who experience social and environmental outcomes. This allows enterprises and investors to maximise their impact by directing resources to those who are most underserved. This page provides guidance on the 'Who' data categories that enterprises and investors can use to collect, assess and report stakeholder data.

Find Open Datasets and Machine Learning Projects

Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Flexible Data Ingestion. We use cookies on Kaggle to deliver our services, analyze web traffic, and

How To Use Deep Learning Even with Small Data

Before we discuss methods for leveraging deep learning for your limited data, please step back from the neural networks and build a simple baseline. It usually doesn't take long to experiment with a few traditional models such as a random forest.

NIH releases first dataset from unprecedented study of

2018/2/13Approximately 30 terabytes of data (about three times the size of the Library of Congress collection), obtained from the first 4,500 participants, will be available to scientists worldwide to conduct research on the many factors that influence brain, cognitive, social, and

AI Challenger : A Large

Significant progress has been achieved in Computer Vision by leveraging large-scale image datasets. However, large-scale datasets for complex Computer Vision tasks beyond classification are still limited. This paper proposed a large-scale dataset named AIC (AI Challenger) with three sub-datasets, human keypoint detection (HKD), large-scale attribute dataset (LAD) and image Chinese captioning

Online transfer learning by leveraging multiple source

2017/1/11Transfer learning aims to enhance performance in a target domain by exploiting useful information from auxiliary or source domains when the labeled data in the target domain are insufficient or difficult to acquire. In some real-world applications, the data of source domain are provided in advance, but the data of target domain may arrive in a stream fashion. This kind of problem is known as

Frontiers

Introduction Hepatitis B is a viral infection that primarily affects the liver of infected individuals, and can cause both acute and chronic disease. The WHO estimates that 257 million people had a chronic hepatitis B infection in 2015 (), with nearly one million deaths occurring as a result of hepatitis B infections causing cirrhosis and liver cancer.

Arla leveraging data to decarbonise dairy: 'There can be a

2021/4/28Dairy cooperative Arla has developed Climate Checks, a programme that leverages the power of big data to support a transition to low-carbon production. Climate Checks offer 'a proof point that there can be a sustainable future for dairy', Chairman Jan Toft Nrgaard

How To Use Deep Learning Even with Small Data

Before we discuss methods for leveraging deep learning for your limited data, please step back from the neural networks and build a simple baseline. It usually doesn't take long to experiment with a few traditional models such as a random forest.

Leveraging Geospatial Resources

By leveraging this database, efforts to identify and account for areas of wetlands change (i.e. restoration gains) can be better understood and managed throughout the region. 4. The system is designed to provide for a suite of user-friendly query and analysis tools to help users discover and analyze aggregated wetlands datasets.

Data Management in Anaplan: Leveraging Anaplan

If you would like to know how to achieve a clean and reliable baseline data, ready for running your planning processes or what-if scenarios, please feel free to contact us. At Olivehorse, we offer a free taster session where we will spend half a day, on site with your team, and we will demonstrate how to improve your business processes and improve your return on investment.

Frontiers

Introduction Hepatitis B is a viral infection that primarily affects the liver of infected individuals, and can cause both acute and chronic disease. The WHO estimates that 257 million people had a chronic hepatitis B infection in 2015 (), with nearly one million deaths occurring as a result of hepatitis B infections causing cirrhosis and liver cancer.

Leveraging Predictive Analytics to Derive Patient

h3 Leveraging Predictive Analytics to Derive Patient Adherence Drivers Ewa J. Kleczyk, Ph.D., Executive Director, Commercial Effectiveness Analytics, Symphony Health Solutions and Derek Evans, Senior Vice President, Symphony Health Solutions Abstract: Understanding therapy adherence and its factors is an important part of managing healthcare costs and improving patients' health outcomes

AI Papers to Read in 2020. Reading suggestions to keep

#9 The Lottery Ticket Hypothesis (2019) Frankle, Jonathan, and Michael Carbin. "The lottery ticket hypothesis: Finding sparse, trainable neural networks." arXiv preprint arXiv:1803.03635 (2018). Continuing on the theoretical papers, Frankle et al. found that if you train a big network, prune all low-valued weights, rollback the pruned network, and train again, you will get a better

Congruity360

Comprehensive management portal identifies data qualifying for review and queues files for each data stakeholder to manually evaluate Remove barriers dividing your IT, legal, and operations teams that stem from differences in data management to enable one universal governance strategy

Digitizing omics profiles by divergence from a baseline

Technological advances enable increasingly comprehensive profiling of the molecular landscapes of cells, and these data can inform the personalized treatment of complex diseases. Two major obstacles are the complexity of these data and the high degree of person-to-person heterogeneity. We develop a highly simplified, personalized data representation by comparing the profile of an individual to

Datasets For Deep Learning

A complete guide for datasets for deep learning. Here is the list of 25 open datasets for deep learning you should work with to improve your DL skills. A machine translation researcher here, Regarding the machine translation data set you present: You clearly have

Frontiers

BackgroundVaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts.MethodsWe applied cutting edge multi-omics approaches to extensively characterize temporal

HGV2012: Leveraging Next‐Generation Technology and

The availability of large datasets produced by next‐generation technology has accelerated research on disease and clinical phenotypes. New technology has spurred the development of new methods, presented here, that are strongly impacting how researchers address and understand human health, population genetics, and genome characteristics including and beyond DNA sequence.

Property Datasets Spanning of the US Housing Market

Comprehensive, multi-sourced and verified datasets, backed by the industry's foremost data experts, give First American Data Analytics the most expansive and highest quality data in the industry. Our solutions are powered by pairing mortgage loan-level datasets with our proprietary property data, that spans of the US housing market.

Multi‐metric domain adaptation for unsupervised transfer

Comprehensive experiments on eight large‐scale publicly available image classification datasets validate the effectiveness of MMDA methods. In the future, we plan to extend our idea to challenging heterogeneous domain adaptation scenarios, such as source and

Leveraging Uncertainty from Deep Learning for

2021/5/4In this paper, we leverage predictive uncertainty of deep neural networks to answer challenging questions material scientists usually encounter in machine learning-based material application workflows. First, we show that by leveraging predictive uncertainty, a user can determine the required training data set size to achieve a certain classification accuracy. Next, we propose

Mastering Microsoft Power BI

Additionally, business-controlled datasets can introduce version conflicts with corporate semantic models and generally lack the resilience, performance, and scalability of IT-owned datasets. Note It's usually necessary or at least beneficial for BI organizations to own the Power BI datasets or at least the datasets which support important, widely distributed reports and dashboards.

Application of Machine Learning for Tumor Growth

The following baseline patient characteristics were tested to explain variability in OS: age, , body weight (BWT), Eastern Cooperative Oncology Group (ECOG) performance status, smoking status (never smokers vs. other), total protein, albumin, alkaline

A Comprehensive Survey on Machine Learning Techniques for

2021/4/25contributions in the literature leveraging ML for mobile malware detection on the Android platform, most of them rely on diverse metrics, classification models, and performance im-provement techniques. The absence of a common baseline in this field can cause

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