ai-in-life-sciences-trends-and-terms-that-executives-need-to-know

AI in Life Sciences Trends and Terms that Executives Need to Know

Artificial intelligence has already established a small but growing presence in the life sciences industry today, starting with drug discovery and development and now in emerging applications across the product life cycle.

Artificial Intelligence Initiatives at India’s Top IT Services Firms

Artificial Intelligence Initiatives at India’s Top IT Services Firms

To stay competitive and relevant in the fast-changing world led by digital, India’s leading IT services companies, well-known for their cost-competitiveness, have begun leveraging more artificial intelligence (AI) initiatives as the technology has continued to gain traction.

Machine Learning in the Chemical Industry

Machine Learning in the Chemical Industry – BASF, DOW, Royal Dutch Shell, and More

In a white paper about the digitalization of the chemistry and advanced materials sector published by the World Economic Forum and Accenture, total global chemical sales in 2014 amounted to $3.5 trillion and is expected to rise to $6.9 trillion by 2030.

Artificial Intelligence for Content Marketing and Content Creation

Artificial Intelligence for Content Marketing and Content Creation

Episode Summary: Natural Language Processing (NLP) can be applied to tasks such as customer service handling or in chatbots to answer fact based questions. Another emerging application for NLP is in content marketing and content production.

AI in Disney, Viacom, and Entertainment Giants

Artificial Intelligence at Disney, Viacom, and Other Entertainment Giants

Artificial intelligence has found its way in different areas in the entertainment industry from offering customized recommendations on your Friday night movies (as in the case of Netflix) to delivering sports match highlights during live TV coverage. In the latter, this was made possible in the 2017 U.S. Open Tennis Championships when IBM Watson Media used its AI tool to showcase play highlights right after they occur.

3 Waves of AI Transformation in Industry - Pattern Matching, Ubiquitous Access, and Deductive Reasoning

3 Waves of AI Transformation in Industry – Pattern Matching, Ubiquitous Access, and Deductive Reasoning

The following article has been written by Josh Sutton, Global Head, Data & Artificial Intelligence at Publicis.Sapient. Publicis is one of the world's largest. Editing and formatting added by the Emerj team. For information about our thought leadership and publishing arrangements with brands, please visit our partnerships page.

How AI and IoT Are Gradually Entering Indian Telecom Companies

How AI and IoT Are Gradually Entering Indian Telecom Companies

The Indian telecom sector has been going through consolidation phase with the major players vying for the lucrative data services market, which is estimated to be worth 950 billion rupees by 2020, growing at a compounded annual rate of 21 percent, as per a report from Business Line. Bharti Airtel has consolidated its position as the No. 1 player with its acquisition of Tata Teleservices’ mobile business and Vodafone’s acquisition of Idea will really change the pecking order, the report suggested.

Diagnosing and Treating Depression Using AI/ML

Diagnosing and Treating Depression with AI and Machine Learning

Depression is a leading mental disorder impacting about 16 million Americans. According to the World Health Organization, the annual global economic impact of depression is estimated at $1 trillion and is projected to be the leading cause of disability by 2020.

Machine Learning for Managing Diabetes: 5 Current Use Cases

Machine Learning for Managing Diabetes: 5 Current Use Cases

Diabetes is a leading chronic disease that affects more than 30 million people in the United States. The disease results from high blood glucose (blood sugar) due to an inability to properly derive energy from food, primarily in the form of glucose. Insulin is a hormone that normally helps process glucose in the body. However, in the case of diabetes, insulin is inadequate (Type 2 diabetes) or obsolete (Type 1 diabetes).

Machine Learning for Healthcare Operations Software -

Machine Learning for Healthcare Operations Software – Risk Management, Clinical Care, and More

The healthcare analytics market continues to gain traction as the healthcare industry transitions to a value-based care model. Value-based care focuses on quality of care delivery as opposed to volume of patients served. There are great opportunities for data analytics due to the high volume of information that must be routinely collected, tracked and interpreted, particularly in the hospital setting. Examples of value-based care programs in the hospital setting include the Hospital Value-Based Purchasing (HVBP) Program and the Hospital Readmission Reduction (HRR) Program.

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