Sunday February 17, 2019
Home Lead Story Dell EMC Anno...

Dell EMC Announces New Solutions Based on Artificial Intelligence

According to an IDC estimate, 40 per cent of digital transformation initiatives will use AI services by 2019

0
//
credit: www.news.filehippo.com

To help organisations realise the full potential of Artificial Intelligence (AI), Dell EMC on Tuesday announced new solutions designed to simplify the AI environment and accelerate its adoption.

With the new “Ready Solutions for AI”, organisations no longer have to individually source and piece together their own solutions, Dell EMC said in a statement.

Instead, they can rely on a Dell EMC-designed and validated set of best-of-breed technologies for software – including AI frameworks and libraries – with compute, networking and storage, the company added.

Dell EMC said its portfolio of services, including consultation, deployment and support, among others, helps customers drive the rapid adoption and optimisation of their AI environments.

“There’s no doubt that AI is the future, and our customers are preparing for it now,” said Tom Burns, Senior Vice President, Networking and Solutions, Dell EMC.

Dell EMC
Dell EMC releases new AI solutions for digital transformation. Pixabay

“Our goal is to lead the industry with the most powerful and fully-integrated AI solutions. What we’re announcing today allows customers at any scale to start seeing better business outcomes and positions them for AI’s increasingly important role in the future,” Burns added.

According to an IDC estimate, 40 per cent of digital transformation initiatives will use AI services by 2019.

Also Read About Facebook’s New Tools- Facebook Introduces New Tools to Protect Elections Globally

The new AI solutions from Dell EMC come with specialised designs for Machine Learning (ML) with Hadoop, an ecosystem of open source components, and Deep Learning with Nvidia, a US-based computer chip manufacturer.

Dell EMC, a part of Dell Technologies, enables organisations to modernise, automate and transform their data centre using industry-leading converged infrastructure, servers, storage and data protection technologies. (IANS)

Next Story

With Ovarian Cancer Deaths Set to Spike by 67%, AI to Rescue: Study

However, the scans cannot give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention

0
Cancer
Cancer Ribbon. Pixabay

With the incidence of ovarian cancer likely to increase by 55 per cent in another 15 years or so, researchers have created an artificial intelligence (AI) software to help best treat ovarian cancer that will pave the way for personalised medicine and expedite relief, a new study says.

The mathematical software tool — TEXLab — can also predict what treatment might be most effective for patients with the World Ovarian Cancer Coalition predicting that deaths will likely increase by 67 per cent by 2035 due to this particular cancer.

The technology can be used to identify patients who are unlikely to respond to standard treatments and offer alternatives as ovarian cancer is the sixth most common cancer in women in the UK that usually strikes after menopause or those with a family history of the disease.

Early detection of the disease could improve survival rates, the study noted.

“Long-term survival rate for patients with advanced ovarian cancer is poor despite advancements in treatments. There is an urgent need for new ways,” said lead author Eric Aboagye, Professor at Imperial College London.

For the study, researchers used the software to identify the aggressiveness of tumours in CT scans and tissue samples from 364 women with ovarian cancer.

The patients were then given a score known as Radiomic Prognostic Vector (RPV) which indicates how severe the disease is, ranging from mild to severe.

Cancer patient
Cancer patient.

The findings, published in Nature Communications, showed that the software was up to four times more accurate for predicting deaths from ovarian cancer than standard methods.

In addition, five per cent of patients with high RPV scores had a survival rate of less than two years, results showed.

High RPV was also associated with chemotherapy resistance and poor surgical outcomes, suggesting that RPV can be used as a potential bio-marker to predict how patients would respond to treatments.

“Our technology is able to give clinicians more detailed and accurate information on how the patients are likely to respond to different treatments, which could enable them to make better and more targeted treatment decisions,” said Aboagye.

Also Read- AI Can Help Improve Understanding of Earth Science

Doctors as of now diagnose ovarian cancer in a number of ways, including a blood test followed by a CT scan that uses X-rays and a computer to create detailed pictures of the ovarian tumour.

This helps clinicians know how far the disease has spread and determines the type of treatment patients receive, such as surgery and chemotherapy.

However, the scans cannot give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention. (IANS)