About Sollers

Sollers is a graduate school located in New Jersey, specializing in clinical research, drug safety and pharmacovigilance training.

Our graduate certificate and masters programs cover a wide range of subjects tailored to this fast growing industry, and our graduates go on to highly successful careers in the pharmaceuticals industry and healthcare industries.

  • HOURS
  • Monday - Thursday | 10 AM - 7 PM
  • Friday | 12 PM - Midnight
  • Saturday | 12 PM - Midnight
  • Sunday | Closed
  • OPEN 24/7 - sollers.edu
    • PHONE
    • (848) 299-5900
    • Location
    • 100 Menlo Park, Suite 550
      Edison New Jersey 08837 -2488

Location

Call Us Now: 848 299-5900

Sollers Blog

Changing Scenario of Data Science

Posted by Doctor Erick on Oct 30, 2017 1:59:56 PM

Data science is witnessing exponential growth and there is humungous demand for skilled workforce across all types of industries. However, the top data scientists have some fundamental traits that set them apart from the crowd, say an InfoWorld report.

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Topics: Data Science

Healthcare Data Science for Quality Improvement and Patient Safety

Posted by Doctor Dan on Oct 17, 2017 1:47:00 PM

In order to reap the benefits of data, it calls for evolving an organization-wide data science strategy. What with many other segments such as banking has adopted Data Science, health care is an exception. With the absence of a data science strategy, healthcare firms find it difficult to handle the increasing volume of data. Also individual clinicians find it cumbersome to improve the safety, quality and efficiency of the care they provide. An effective data science strategy for health care organizations is therefore, the need of the hour, says, a catalyst.nejm.org report. Data Science has five key components.

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Topics: Data Science

Natural Language Processing Market to touch $22.3 billion by 2025

Posted by Doctor Erick on Sep 29, 2017 2:32:00 PM

Natural language processing (NLP) is a technology spawned from the need for machines to understand and communicate with humans in human language, not formal computer languages, says a company statement.

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Topics: Data Science

Reasons Why Healthcare Should Have Data Science

Posted by Phil on Sep 21, 2017 12:05:16 PM

Big data has made great inroads into a slew of industries. Healthcare, being one of the big and complex industries in the US, it is ideal for big data initiatives.

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Topics: Data Science

Data Capture Methods- eCOA and ePRO

Posted by Phil on Sep 11, 2017 10:35:56 AM

Over the recent years, the data capture technology has influenced a large sector of business organizations in terms of novel approaches and seamless execution. Electronic clinical outcome assessments and Electronic patient report assessments follow methodologies that are appropriate for effective data capture mechanisms. Both of these technology-enabled methods project a comprehensive space into user's everyday lives for using their device-inclusive approach i.e. the data captured can be accessed from any internet connected device such as mobile phones, laptops, tablets, medical devices, and PCs.

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Topics: Data Science

Importance of Tableau in Data Analytics

Posted by Phil on Sep 1, 2017 2:32:06 PM

Tableau enables businesses to make decisions using the data visualization features available to business users of any background and Industry. It empowers businesses to keep up with the continuously evolving technology and outperform its competition through an innovative means of visualizing their data. There is not a single data source that Tableau fails to connect with. Let it be Data Warehouse, MS Excel or any web data, it establishes a connection with all of them. Basically, in any type of data analytics, Tableau provides an end to end insight by transforming data into visually engaging, interactive views in dashboards. With easy to use drag-and-drop interface one can come up with insights in few moments rather than months or years.

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Topics: Data Science

Recent trends in Neuromorphic Engineering

Posted by Phil on Aug 30, 2017 3:14:35 PM

Technology is changing the world at an unimaginable speed. It has been the greatest transformation tool in the modern world. From the age of Industrial revolution, the world has changed completely. Today, we cannot imagine our life without technology.

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Topics: Data Science

How Artificial Intelligence Is Helping The Pharmaceutical Industries?

Posted by Phil on Aug 23, 2017 3:53:09 PM

The current drug discovery process needs to shift dramatically in order to meet the needs of both the society and patients in the 21st Century. Artificial Intelligence and machine learning, in particular, present the pharmaceutical industry with a real opportunity to do R&D differently, so that it can operate more efficiently and substantially improve success at the early stages of drug development. There needs to be a fundamental shift in drug discovery and Artificial Intelligence holds the key to bringing the pharmaceutical industry into the 21st Century.

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Topics: Data Science

Data Integrity Risk and Mitigation

Posted by Phil on Aug 22, 2017 12:46:00 PM

The United States Federal Drug Administration (USFDA) defines Data Integrity as data, which is complete, consistent and accurate. It further defines data integrity as data, which is:

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Topics: Data Science

Semantic Indexing Along With Deep Learning

Posted by Phil on Aug 16, 2017 11:14:05 AM

One of the main areas that are trending in the research sectors of Machine Learning and Pattern Recognition is Deep Learning (DL). DL focuses on Machine Learning tools and techniques and applies them in resolving complications which lack human or artificial thoughts and could be achieved in data science. DL is achieved by learning over a cascade of many layers. DL handles many real world complications, such as Machine Translation, Object Recognition, and Localization, Speech Recognition, Image caption generation, Distributed representation for text, Natural Language Processing, Image Classification, etc., with its data-driven representation learning. The traditional computing is facing challenges in dealing with high-dimensional and streaming data, semantic indexing, and scalability of models.

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Topics: Data Science