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Application of Data Science in Healthcare

Application of Data Science in Healthcare

In today’s data-driven world,  it is hard to ignore the growing need for data science, as businesses are busy applying data to devise smarter marketing strategies and urging their employees to upgrade themselves. Data Science training is gaining ground as lucrative career opportunities are beckoning the younger generation.

So, it is not surprising that a crucial sector like healthcare would apply data science to upgrade their service. Health care is among one of the many sectors that have acknowledged the benefits of data science and adopted it.

The Healthcare industry is vast and it comprises many disciplines and branches that intercross generating a ton of unstructured data which if processed and analyzed could lead to revolutionary changes in the field.

Here is taking a look at how the industry can benefit by adopting data science techniques

Diagnostic error prevention

No matter what health issues one might have, accurate diagnosing is the first step that helps a physician prescribe treatment procedure. However, there have been multiple cases where a diagnostic error has led to even death. With the implementation of data science technology, it is now possible to increase the accuracy of the procedures as the algorithm sifts data to detect patterns and come up with accurate results.

Medical imaging procedures such as MRI, X-Ray can now detect even tiniest deformity in the organs which were erstwhile impossible, due to the application of deep learning technology.  Advanced models such as MapReduce is also being put to use to enhance the accuracy level.

Bioinformatics

 Genomics is an interesting field of research where researchers analyze your DNA to understand how it affects your health. As they go through genetic sequences to gain an insight into the correlation, they try to find how certain drugs might work on a specific health issue.

The purpose is to provide a more personalized treatment program. In order to process through the highly valuable genome data, data science tools such as SQL are being applied. This field has a vast scope of improvement and with more advanced research work being conducted in the field of Bioinformatics, we can hope for better results.  Researchers who have studied Data science using python training, would prove to be invaluable assets for this specific field.

Health monitoring with wearables

Healthcare is an ongoing process, if you fall ill, you get yourself diagnosed and then get treatment for the health condition you have. The story in most cases does not end there, with the number of patients with chronic health problems increasing, it is evident that constant monitoring of your health condition is required to prevent your health condition from taking a worse hit.  Data science comes into the picture with wearables and other forms of tracking devices that are programmed to keep your health condition in check. Be it your temperature or, heartbeat the sensors keep tracking even minute changes, the data is analyzed to enable the doctors take preventive measures, the GPS-enabled tracker by Propeller, is an excellent case in point.

Faster approval of new drugs

The application of data science is not restricted to only predicting, preventing, and monitoring patient health conditions. In fact, it has reached out to assist in the drug development process as well. Earlier it would take almost a decade for a drug to be accessible in the market thanks to the numerous testing, trial, and approval procedures.

But, now it is possible to shorten the duration thanks to advanced data science algorithms that enable the researchers to simulate the way a drug might react in the body. Different models are being used by the researchers to process clinical trial data, so, that they can work with different variables. Data Science course enables a professional to carry out research work in such a highly specialized field.

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In the context of Covid-19

With the entire world crippling under the unprecedented impact of COVID-19, it is needless to point out that the significance of data science in the healthcare sector is only going to increase. If you have been monitoring the social media platforms then you must have come across the #FlattenTheCurve.

The enormity of the situation and erroneous data collection both have caused issues, but, that hasn’t deterred the data scientists. Once, the dust settles they will have a mountainous task ahead of them to process through a massive amount of data the pandemic will have left behind, to offer insight that might help us take preventive measures in the future.

The field of data science has no doubt made considerable progress and so has the field of modern healthcare. Further research and collaboration would enable future data scientists to provide a better solution to bolster the healthcare sector.

 


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Top Python Libraries to Know About in 2020

Top Python Libraries To Know About In 2020

Python today is one of the most sought after programming languages in the world. As per Python’s Executive Summary, “Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance.”

The most advantageous facet of Python is the richness of its library sources and the myriad uses and applications of these libraries in programming. This essay is dedicated to studying some of the best Python libraries available.

Tensor Flow

Tensor Flow is a highly popular open source library built by Google and Brain Team. It is used in almost all Google projects for machine learning. Tensor Flow 

works as a computational library for writing fresh algorithms that require vast amounts of tensor operations.

Scikit-learn

Unarguably one of the most competent libraries for working with complex data, Scikit-learn is a python library associated with Numpy and SciPy. This library facilitates cross validation or the ability to use more than one metric.

Keras

Keras is one of the most revolutionary libraries in Python in that it makes it easy to express neural networks. Keras provides some of the most competent utilities for compiling models, processing datasets and more.

PyTorch

It is the largest machine learning library that permits developers to perform tensor computation, create dynamic graphs and calculate gradients automatically. Also, it offers a rich repository of APIs for solving applications related to neural networks.

Light GBM

Gradient Boosting is one of the best machine learning libraries that helps developers build new algorithms using elementary models like decision trees. This library is highly scalable and optimal for fast implementation of gradient boosting.

Eli5

This library helps overcome the problem of inaccuracy in machine learning model predictions. It is used in mathematical operations that consume less computational time and it is important when it comes to depending on other Python libraries.

SciPy

This library is built using Numpy and it is used in high-level computations in data science. It is used extensively for scientific and computations, solving differential equations, linear algebra and optimization algorithms.

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Pandas

Python Data Analysis or Pandas is another highly popular library that is crucial to a data science life cycle in a data science project. Pandas provides super fast and flexible data structures such as data frame CDs that are specifically designed to work with structured data intuitively.

There are many more libraries like Theano and Librosa that are lesser known but very very important for machine learning, the most revolutionary scientific development of our century. To know more on the subject, do peruse the DexLab Analytics website today. DexLab Analytics is a premier Machine Learning institute in Gurgaon.

 


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Why Learning Python is Important for Data Scientists Today

Why Learning Python is Important for Data Scientists Today

Data Science is the new rage and if you are looking to make a career, you might as well choose to become a data scientist. Data Scientists work with large sets of data to draw valuable insights that can be worked upon. Businesses rely on data scientists to sieve through tonnes of data and mine out crucial information that becomes the bedrock of business decisions in the future.

With the growth of AI, machine learning and predictive analytics, data science has come to be one of the favoured career choices in the world today. It is imperative for a data scientist to know one of more programming languages from any of those available – Java, R, Python, Scala or MATLAB.

However, Data Scientists prefer Python to other programming languages because of a number of reasons. Here we delve into some of them.

Popular

Python is one of the most popular programming languages used today. This dynamic language is easy to pick up and learn and is the best option for beginners. Secondly, it interfaces with complex high performance algorithms written in Fortran or C. It is also used for web development, data mining and scientific computing, among others.

Preferred for Data Science

Python solves most of the daily tasks a data scientist is expected to perform. “For data scientists who need to incorporate statistical code into production databases or integrate data with web-based applications, Python is often the ideal choice. It is also ideal for implementing algorithms, which is something that data scientists need to do often,” says a report

Packages

Python has a number of very useful packages tailored for specific functions, including pandas, NumPy and SciPy. Data Scientists working on machine learning tasks find scikit-learn useful and Matplotlib is a perfect solution for graphical representation and data visualization in data science projects.

Easy to learn

It is easy to grasp and that is why not only beginners but busy professionals also choose to learn Python for their data science needs. Compared to R, this programming language shows a sharper learning curve for most people choosing to learn it.

Scalability

Unlike other programming languages, Python is highly scalable and perceptive to change. It is also faster than languages like MATLAB. It facilitates scale and gives data scientists multiple ways to approach a problem. This is one of the reasons why Youtube migrated to Python.

Libraries

Python offers access to a wide range of data science and data analysis libraries. These include pandas, NumPy, SciPy, StatsModels, and scikit-learn. And Python will keep building on these and adding to these.  These libraries have made many hitherto unsolvable problems seem easy to crack for data scientists.

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Python Community

Python has a very robust community and many data science professionals are willing to create new data science libraries for Python users. The Python community is tight-knit one and very active when it comes to finding a solution. Programmers can connect with community members over the Internet and Codementor or Stack Overflow.

So, that is why data scientists tend to opt for Python over other programming languages. This article was brought to you by DexLab Analytics. DexLab Analytics is premiere data science training institute in Gurgaon.

 


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DexLab Analytics Rated One of The Best Institutes in India

DexLab Analytics Rated One of The Best Institutes in India

Analytics India Magazine (AIM), one of the foremost journals on big data and AI in India, has rated Dexlab Analytics’ credit risk modelling course one of the best in India and recommended it be taken up to learn the subject in 2020. Dexlab Analytics is on AIM’s list of nine best online courses on the subject.

In an article, the AIM has rated DexLab Analytics as a premier institute offering a robust course in credit risk modelling. Credit risk modelling is “the analysis of the credit risk that helps in understanding the uncertainty that a lender runs before lending money to borrowers”.

The article describes the Dexlab Analytics course as offering learners “an opportunity to understand the measure of central tendency theorem, measures of dispersion, probability theory and probability distribution, sampling techniques, estimation theory, types of statistical tests, linear regression, logistic regression. Besides, you will learn the application of machine learning algorithms such as Decision tree, Random Forest, XGBoost, Support Vector Machine, banking products and processes, uses of the scorecard, scorecard model development, use of scorecard for designing business strategies of a bank, LGD, PD, EAD, and much more.”

The other bodies offering competent courses on the subject on AIM’s list are Udemy, SAS, Redcliffe Training, EDUCBA, Moneyweb CPD HUB, 365 DataScience and DataCamp.

Analytics India Magazine chronicles technological progress in the space of analytics, artificial intelligence, data science & big data by highlighting the innovations, players, and challenges shaping the future of India through promotion and discussion of ideas and thoughts by smart, ardent, action-oriented individuals who want to change the world.

Since 2012, Analytics India Magazine has been dedicated to passionately championing and promoting the analytics ecosystem in India. We have been a pre-eminent source of news, information and analysis for the Indian analytics ecosystem, covering opinions, analysis, and insights on key breakthroughs and future trends in data-driven technologies as well as highlighting how they’re being leveraged for future impact.

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Dexlab Analytics has been thriving as one of the prominent institutes offering the best selection of courses on Big Data Hadoop, R Programming, Python, Business Analytics, Data Science, Machine Learning, Deep Learning, Data Visualization using Tableau and Excel. Moreover, it aims to achieve Corporate Training Excellence with each training it conducts.

For more information on this, click here – www.prlog.org/12826797-dexlab-analytics-listed-as-one-of-the-best-institutes-in-india.html

 


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