Speaking at KnowDis Machine Learning Day, Avantika Lal - Senior Scientist (Deep Learning and Genomics) at NVIDIA - said larger data sets on genome sequences (DNA arrangement) are being acquired, and this data is being studied for multiple parameters. "As the cost of sequencing goes down, more and more people can get their genome sequence and in fact, governments, research institutes and public health organisations around the world are trying to sequence many thousands of people in order to be build up an idea of the genomes of the populations of their countries," she said. Lal added that massive data sets are collected that are very complicated and contain many different related kinds of information. "...the size and richness of the data sets that we''re now getting in this field makes it really essential to use machine learning and deep learning to analyze this data in order to answer complicated questions like, for example, how do we identify people who are more at risk of developing various diseases before they actually develop signs of those diseases," she said. These data sets can also help understand the mechanisms by which a certain disease arises in people, or how does one identify patients who might respond differently or be more sensitive to a particular kind of drug or treatment, she further said.

Artificial intelligence (AI) and machine learning are helping analyse massive amounts of data around the human genome and drug molecules, and these new-age technologies can play an important role in the fight against Covid-19, industry experts said on Saturday. Speaking at KnowDis Machine Learning Day, Avantika Lal - Senior Scientist (Deep Learning and Genomics) at NVIDIA - said larger data sets on genome sequences (DNA arrangement) are being acquired, and this data is being studied for multiple parameters. "As the cost of sequencing goes down, more and more people can get their genome sequence and in fact, governments, research institutes and public health organisations around the world are trying to sequence many thousands of people in order to be build up an idea of the genomes of the populations of their countries," she said. Lal added that massive data sets are collected that are very complicated and contain many different related kinds of information. "...the size and richness of the data sets that we're now getting in this field makes it really essential to use machine learning and deep learning to analyze this data in order to answer complicated questions like, for example, how do we identify people who are more at risk of developing various diseases before they actually develop signs of those diseases," she said.

BEGIN ARTICLE PREVIEW: NewsBytesTata Motors is offering year-end discounts on these BS6 carsTo end the year on a positive note, Tata Motors is offering great deals on select models such as the Tiago, Tigor, Nexon, and Harrier. These offers are valid till the end of this month and can be availed in the form of cash discounts, exchange bonuses, as well as corporate discounts. Here are more details. END ARTICLE PREVIEW READ MORE FROM SOURCE ARTICLE

I was on the phone recently with a large multinational corporate investor discussing the applications for robotics in the energy market. He expressed his frustration about the lack of products to inspect and repair active oil and gas pipelines, citing too many catastrophic accidents. His point was further endorsed by a Huffington Post article that reported in a twenty-year period such tragedies have led to 534 deaths, more than 2,400 injuries, and more than $7.5 billion in damages. The study concluded that an incident occurs every 30 hours across America's vast transcontinental pipelines. The global market for pipeline inspection robots is estimated to exceed $2 billion in the next six years, more than tripling today's $600 million in sales.

In this guest column, Adam Rogers, chief technology officer of Ultimate Software, describes where he believes AI and machine learning will lead HCM technology. Despite the intrinsic contradiction, it's clear that artificial intelligence and machine learning are primed to play a leading role in the future of human capital management. As CTO of a software company that offers AI-driven HCM solutions across a variety of industries, I've had the opportunity to witness this growing impact first-hand and think about where these technologies will take us moving forward. Recent advancements have already eliminated tedious payroll tasks, improved employee productivity and streamlined processes. But as technology continues to evolve at a breakneck pace, emerging systems are looking to revolutionize how organizations make hiring, firing and compensation decisions.

Artificial intelligence or AI as it is called in cyber parlance, and believed to be the next big thing in information and technology, can play a key role in good governance, a senior Microsoft official has said. "We are seeing that governments are benefitting through Artificial Intelligence and are able to bring (governance) closer to people in their countries," Dave Forstrom, director of communications for the Artificial Intelligence (AI) group at Microsoft, told PTI. "Absolutely," he answered when asked if AI can be a tool in good governance. "In terms of helping create good governance we're seeing an approach industry--wide right now where it's focused on ethical design and those principles that will help to really govern that," he said on the sidelines of the Microsoft's annual developers conference Build 2017. Microsoft's India-born CEO Satya Nadella has identified AI as the center piece of the company's growth strategy. Forstrom said Microsoft is having partnerships with a number of governments in this regard. "Singapore is one that we recently worked with last year to actually help them create bots to better engage their customers," he said.

AI is also being used in other areas of healthcare including analyzing data to help patients take their medications on time, manage diabetes and improve clinical practices in mental health. "Artificial intelligence can help providers gain insights about their patients, their treatments and their workflow that they could never have known on their own" said Harpreet Singh Buttar, transformational health industry analyst at Mountain View, California-based, research firm Frost & Sullivan. He added that by using this technology, doctors will achieve their population health management goals as they make better decisions at a much faster rate. Furthermore, computational computing can be applied to many data sets associated with population health management including data registries, electronic health records, data generated from team care, as well as claims data, information gleaned from hospital readmissions and data related to social determinants that have a significant impact on patient populations. Frost & Sullivan estimates that the market for AI will grow from earned revenues of $634 million in 2014 to $6.6 billion in 2021 at a compound annual growth rate of 40%.

The increasing use of artificial intelligence (AI) to analyze large patient data sets promises to change the face of population health management in a way that will be far reaching across the industry and a game changer to the way physicians monitor and care for their patients. AI's ability to raise the level of evidence-based medicine can help primary care physicians make better decisions in several areas. These include the ability to determine appropriate treatments for their patients and to how best to monitor their care during and after hospitalization, to improving efficiency and productivity in care team workflows and finding better ways to reduce overall costs associated with patient care. Supercomputers that compare and analyze large groups of patients' clinical data, diagnostic images and claims data, are capable of identifying subtle patterns and changes in health and wellness that can foreshadow the start of an illness, monitor the effectiveness of drug treatments and identify patients' health risks. For example, when researchers at the MRC London Institute of Medical Sciences, wanted to find out which patients with pulmonary hypertension had the greatest risk of heart failure, they used AI software to analyze images of patients' hearts and constructed a smart 3D heart that predicts patient survival rates.