Advertisement

Present and Future of Artificial Intelligence in Medicine | Analytics Insight

present and future of artificial intelligence in medicine | analytics insight

BEGIN ARTICLE PREVIEW:


August 15, 2020
0 comments

Artificial intelligence (AI) is the technological new trend currently providing more options for businesses to strive. Just like any other profession, medicine is also having a taste of Artificial intelligence. According to various medical researches, about 50 percent of activities carried out by workers can be automated.
How medical practitioners respond to the use of AI is important to its success. For instance, 25 years ago, certain medical innovations were almost impossible. 
As a matter of fact, AI has contributed immensely to medicine but what does the future hold for medicine.

What is artificial intelligence in medicine?
Artificial intelligence is the use of AI technology, also known as ‘automated processes’ in the diagnosis and treatment of patients that require medical attention.

Although diagnosis and treatment could seem much like basic processes, nevertheless several other background procedures must be carried out for a patient to go through proper recovery. Below are some of the processes;

Garnering patient’s data through tests and interviews
Processing and analyzing test results
Utilization of different data sources to come up with an accurate diagnosis. 
Resolving on a proper treatment process
Preparing and administering the preferred method of treatment
Monitoring patient
Post – care, follow-ups and appointments

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE

“The ‘AI’ Cosmos” –Intelligent Algorithms Begin Processing the Universe | The Daily Galaxy

“the ‘ai’ cosmos” –intelligent algorithms begin processing the universe | the daily galaxy

BEGIN ARTICLE PREVIEW:

This June, 2020, NASA announced that intelligent computer systems will be installed on space probes to direct the search for life on distant planets and moons, starting with the 2022/23 ESA ExoMars mission, before moving beyond to moons such as Jupiter’s Europa, and of Saturn’s Enceladus and Titan.“This is a visionary step in space exploration.” said NASA researcher Victoria Da Poian. “It means that over time we’ll have moved from the idea that humans are involved with nearly everything in space, to the idea that computers are equipped with intelligent systems, and they are trained to make some decisions and are able to transmit in priority the most interesting or time-critical information”.“When first gathered, the data produced by the Mars Organic Molecule Analyzer (MOMA) toaster-sized life-searching instrument will not shout out ‘I’ve found life here’, but will give us probabilities which will need to be analyzed,” says Eric Lyness, software lead in the Planetary Environments Lab at NASA Goddard Space Flight Center. “We’ll still need humans to interpret the findings, but the first filter will be the AI system”.“Is There Life There, HAL?” –NASA Announces Intelligent AI Systems Installed on Probes of Distant PlanetsClassifying …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading ““The ‘AI’ Cosmos” –Intelligent Algorithms Begin Processing the Universe | The Daily Galaxy”

Everything You Need To Know About Machine Learning In Unity 3D

everything you need to know about machine learning in unity 3d

BEGIN ARTICLE PREVIEW:

Unity 3D is a popular platform for creating and operating interactive, real-time 3D content. It is a cross-platform 3D engine and a user-friendly integrated development environment (IDE) which helps in creating games in 3D as well as applications for desktop, mobile, web and more. It consists of a number of tools for programmers as well as artists to create real-time solutions, such as films and automotive, apart from games. The flexible real-time tools of Unity offer incredible possibilities for all industries and applications. 

With a vision to maximise the transformative impact of Machine Learning for researchers and developers, Unity released the first version of Unity Machine Learning Agents Toolkit (ML-Agents) in 2017. 

The aim of this ML environment is to allow game developers and AI researchers to use Unity as a platform to train as well as embed intelligent agents with the help of the latest advancements in ML and AI. 

Unity ML-Agents Toolkit

The Unity Machine Learning Agents Toolkit or simply ML-Agents is an open-source project by Unity, which allows games and simulations to serve as environments for training the intelligent agents. ML-Agents includes a C#  software development kit (SDK) to set up a scene and define the agents within …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Everything You Need To Know About Machine Learning In Unity 3D”

Melting ‘frozen memories,’ artificial intelligence helps Japanese recall days of World War II

melting ‘frozen memories,’ artificial intelligence helps japanese recall days of world war ii

BEGIN ARTICLE PREVIEW:

Return to homepage ×

Please subscribe to keep reading. You can cancel at any time.

Already a subscriber?

[class*=’col-‘].featured-package .title { background-color: #0d6ea1 }
#lee-services-list.multiple .row > [class*=’col-‘].featured-package .triangle { border-color: #0d6ea1 transparent; }
#lee-services-list.multiple .featured-package .label-tag { background-color: #335262 }
}
]]>

Loading&hellp;

‘);
$(‘.lee-featured-subscription’).html(sFallBack);
}

function lee_formatPackage(oService){
try {
var bOnlyModal = true;
var oSettings = lee_getPackageSettings(oService.HomeMembership);
var newService = {};
if(parseInt(oService.WebFeatureFG) === 2) return false;
if(oService.WebStartPrice != ”){
var custom = JSON.parse(oService.WebStartPrice);
$.each(custom, function(k,v){
newService[k] = v;
});
}
if(bOnlyModal && newService.in_modal && newService.in_modal.toLowerCase() === ‘false’) return false;
if(!bOnlyModal && newService.not_members && newService.not_members.toLowerCase() === ‘true’) return false;

newService.has_featured_class = newService.featured ? ‘featured-package’ : ”;
newService.sort = parseInt((newService.sort) ? newService.sort : oSettings.sort);
newService.title = oSettings.title;
newService.level = oService.HomeMembership;
newService.html = oService.WebOfferHTML;
newService.disabled = newService.disable_purchase ? ‘disabled’ : ”;

var price = lee_formatPackagePrice(newService.start_price);
newService.start_price = price.cost;
newService.format_dollars = (price.format_dollars) ? price.format_dollars : ”;
newService.format_cents = (price.format_cents) ? price.format_cents : ”;
newService.start_at_rate = (newService.fixed_rate === ‘true’) ? ‘for the low price of’ : ‘starting at’;

if( !newService.term ) newService.term = …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Melting ‘frozen memories,’ artificial intelligence helps Japanese recall days of World War II”

How Facebook’s Yann LeCun is charting a path to human-level artificial intelligence

how facebook’s yann lecun is charting a path to human-level artificial intelligence

BEGIN ARTICLE PREVIEW:

When Yann LeCun founded the Facebook AI Research (FAIR) lab in 2013, artificial intelligence was entering a boom period that his research helped trigger.  
Facebook’s chief AI scientist had been among a group of computer scientists who retained faith in deep neural networks during an “AI winter” of reduced funding and interest in the field. In 2019, his efforts earned him a share of the Turning Award, together with his friends Yoshua Bengio and Geoffrey Hinton. 

Today, AI is now an essential component of Facebook’s vast array of applications, touching everything from Messenger to content moderation.
“You take AI out of Facebook, and basically the services crumble,” LeCun tells TNW.
But fears are now emerging that another winter will soon arrive if AI can’t live up to its current hype, particularly around the promise of artificial general intelligence (AGI): the idea that a machine can perform any intellectual task a human can — and many that they can’t.
LeCun is not a fan of the term. He’s previously argued that “there is no such thing as AGI” because “human intelligence is nowhere near general.” However, he is keenly pursuing “human-level AI.” His chosen technique for reaching it is …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “How Facebook’s Yann LeCun is charting a path to human-level artificial intelligence”

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients

the deep learning model combining ct image and clinicopathological information for predicting alk fusion status and response to alk-tki therapy in non-small cell lung cancer patients

BEGIN ARTICLE PREVIEW:

This article was originally published here
Eur J Nucl Med Mol Imaging. 2020 Aug 13. doi: 10.1007/s00259-020-04986-6. Online ahead of print.

ABSTRACT
PURPOSE: This study aimed to investigate the deep learning model (DLM) combining computed tomography (CT) images and clinicopathological information for predicting anaplastic lymphoma kinase (ALK) fusion status in non-small cell lung cancer (NSCLC) patients.
MATERIALS AND METHODS: Preoperative CT images, clinicopathological information as well as the ALK fusion status from 937 patients in three hospitals were retrospectively collected to train and validate the DLM for the prediction of ALK fusion status in tumors. Another cohort of patients (n = 91) received ALK tyrosine kinase inhibitor (TKI) treatment was also included to evaluate the value of the DLM in predicting the clinical outcomes of the patients.
RESULTS: The performances of the DLM trained only by CT images in the primary and validation cohorts were AUC = 0.8046 (95% CI 0.7715-0.8378) and AUC = 0.7754 (95% CI 0.7199-0.8310), respectively, while the DLM trained by both CT images and clinicopathological information exhibited better performance for the prediction of ALK fusion status (AUC = 0.8540, 95% CI 0.8257-0.8823 in the primary cohort, p < 0.001; AUC = 0.8481, 95% CI 0.8036-0.8926 in the validation cohort, p < 0.001). In addition, the deep learning scores of the DLMs showed significant differences ... END ARTICLE PREVIEW READ MORE FROM SOURCE ARTICLE Continue reading “The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients”

Savan Group Delivers Cloud-Based Artificial Intelligence and Machine Learning Capability

savan group delivers cloud-based artificial intelligence and machine learning capability

BEGIN ARTICLE PREVIEW:

MCLEAN, Va., Aug. 14, 2020 /PRNewswire/ — Today, Savan Group, a leader in advanced data analytics and visualization, announced that it has partnered with Amazon Web Services (AWS) to establish a cloud-based artificial intelligence (AI) and machine learning (ML) platform. Savan Group continues to apply state-of-the-art AI solutions to address the data and information challenges of the Federal Government. Savan Group is now developing ML models with near unlimited scale using distributed cloud storage and GPU compute within a FedRAMP-authorized environment.
The Federal Government is under increasing pressure to fully leverage the value of data for mission, service, and public good. Unfortunately, much of this data is locked away in documents, videos, audio, images, and paper. Additionally, the creation of unstructured data is rapidly outpacing the ability for organizations to manage, govern, and recognize its value. Leveraging ML and natural language processing (NLP), Savan Group is analyzing and extracting untapped potential, turning data into information and information into knowledge. With AWS, Savan Group is taking its ML capability to the next level with greater time to innovation and at a lower cost.
“The ability to leverage distributed cloud processing enables Savan Group to rapidly develop, test, and execute its ML models. This …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Savan Group Delivers Cloud-Based Artificial Intelligence and Machine Learning Capability”

Quantum Computing: What Does It Mean For AI (Artificial Intelligence)?

quantum computing: what does it mean for ai (artificial intelligence)?

BEGIN ARTICLE PREVIEW:

LAS VEGAS, NV – JANUARY 08: Intel Corp. CEO Brian Krzanich delivers a keynote address at CES 2018 … [+] at Park Theater at Monte Carlo Resort and Casino in Las Vegas on January 8, 2018 in Las Vegas, Nevada. CES, the world’s largest annual consumer technology trade show, runs from January 9-12 and features about 3,900 exhibitors showing off their latest products and services to more than 170,000 attendees. (Photo by Ethan Miller/Getty Images)

Getty Images

While quantum computing is still in the early phases, there have already been many innovations and breakthroughs. Companies like IBM, Microsoft, Google and Honeywell have been investing aggressively in the technology. 
So then what is quantum computing? Well, it is similar to traditional computing, which relies on bits—that is, the 0’s and 1’s to encode information. But quantum computing as its own version of this: the quantum bit or qubit. This is where the information can have multiple states at the same time. And the reason for this is the impact of the effects of quantum mechanics, like superposition and entanglement. Yes, this is all about the spooky world of Schrodinger’s cat, which is both alive and dead at the same time!
“Quantum computing is a new kind …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Quantum Computing: What Does It Mean For AI (Artificial Intelligence)?”

Chip startup Blaize debuts AI modules for machine learning at the edge

chip startup blaize debuts ai modules for machine learning at the edge

BEGIN ARTICLE PREVIEW:

Venture-backed chip startup Blaize Inc. has introduced three new hardware modules for running artificial intelligence models at so-called edge locations such as factories.
The modules, announced on Thursday, are based on the Graph Streaming Processor that the startup first previewed last November. That’s the month Blaize exited stealth mode with $87 million in funding from investors including Samsung Electronics Co. Ltd.’s Catalyst Fund and Daimler AG.
Blaize’s Graph Streaming Processor or GSP is a chip designed specifically to run artificial intelligence models. It performs this task up to 60 times more efficiently than traditional central processing units and graphics cards, according to the startup. The chip can manage as many as 16 trillion operations per second while consuming about seven watts of power, which is on par with the electricity consumption of a smart light bulb.
The GSP’s efficiency is the result of a highly specialized chip architecture. At the software level, neural networks can be implemented in the form of a data structure known as a graph, and Blaize has equipped the GSP with optimizations specifically designed to run such graphs. One of the main optimizations is a feature that saves electricity by lowering the number of times …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Chip startup Blaize debuts AI modules for machine learning at the edge”

Artificial intelligence camera can identify different bird species for you

iam platform login page background

BEGIN ARTICLE PREVIEW:

Read full article In The KnowArtificial intelligence camera can identify different bird species for youAlex LaskerAugust 14, 2020, 8:03 AMBird watching just got a whole lot more high tech.Birdsy, a wildlife-spotting camera, has developed a unique artificial intelligence (AI) that records and identifies birds and other animals all by itself, meaning you never have to miss out on priceless nature moments again.The Wi-Fi-connected camera can monitor your bird feeders and yard 24/7, identify each species it spots, record and log each animal visitor, and send the data directly to a smartphone app for you to enjoy.The app even makes it easy to share your favorite bird spots on social media. Credit: BirdsySince Birdsy was launched on Kickstarter, it has raced past its original goal of $60,000, with 506 backers pledging a total of $114,790 to help bring the project to life.Birdsy’s AI is constantly learning and changing. Currently, it is able to identify species in North America and Europe and, with the power of ultra-fast Verizon 5G, the number of birds and other animals it can recognize will continue to grow.Watch the futuristic gadget in action in the video above.If you enjoyed this article, check out the Hollywood sci-fi technology …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Artificial intelligence camera can identify different bird species for you”