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How Generalizable Are Radiology AI Algorithms?

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How Generalizable Are Radiology AI Algorithms?

Over 80 percent of the 86 algorithms reported in the study performed poorly on external datasets.

A team of researchers from the Johns Hopkins University School of Medicine systematically assessed 83 peer-reviewed studies on deep-learning algorithms that perform image-based radiologic prediction and have received external validation. Over 80 percent of the 86 algorithms reported in the study performed poorly on external datasets, and 24 percent performed significantly worse.

“Our findings emphasise the need of using an external dataset to assess the generalizability of deep-learning algorithms, which may improve the quality of future deep-learning research,” stated by Bahram Mohajer, Drs. Alice Yu, and John Eng.

The researchers wanted to get a better estimate of the algorithms’ generalizability, or how well the algorithms perform on knowledge from various establishments vs knowledge they had been trained on. The 3 researchers independently examined study titles and abstracts to choose related publications for inclusion in their evaluation after searching the PubMed database for English-language research.

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They concentrated on studies that detailed algorithms that performed diagnostic classification duties. Articles about nonimaging scientific solutions or tactics other than deep research were not accepted. Ultimately, 83 peer-reviewed studies covering 86 methods were included in the final assessment.

41 (48 percent) were concerned with the chest, 14 (16 percent) with the mind, 10 (12 percent) with the bone, seven (8 percent) with the stomach, and 5 (6 percent) with the breast. The remaining 9 algorithms dealt with various aspects of the human body.

On a per-modality basis, nearly 75% used both radiography and CT. The authors noted that just three studies collected prospective knowledge for either the event or the external validation dataset. Furthermore, the dataset dimensions and disease incidence varied widely, and the outside datasets were significantly smaller than the event datasets (p 0.001).

The researchers then calculated the difference in the area beneath the curve to compare the performance of the algorithms on the internal and external datasets (AUC). Of the 86 algorithms tested, 70 (81 percent) performed poorly on the outside check units.

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Change in AI algorithm efficiency when used on the exterior validation dataset
Substantial improvement (≥ 0.10 in AUC) inefficiency Modest improvement (≥ 0.05 in AUC) inefficiency Little change inefficiency Modest lower (≥ 0.05 in AUC) inefficiency Substantial lower (≥ 0.10 in AUC) inefficiency
Change inefficiency 1.1% 3.5% 46.5% 24.4% 24.4%

The researchers contend that it is mainly unknown why deep-learning systems perform poorly on external datasets.

“Questions remain about what options are literally required for successful prediction by machine learning algorithms, how these options can be biassed in datasets, and how exterior validation is influenced,” the authors stated. “A better grasp of these concerns will be required before diagnostic machine studying algorithms can be used in ordinary scientific radiology practise.”

 

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AI Will Take Over Your House Through Smart Home Technology

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AI Will Take Over Your House Through Smart Home Technology

As artificial intelligence (AI) aids smart gadgets in making daily tasks easier; they are becoming safer

Smart home technologies enhance household appliances, home safety and security, lighting, and entertainment. Key sectors have begun to combine artificial intelligence with smart gadgets to improve connectivity. AI is described as the ability to connect several IoT devices, as well as improved processing and learning capabilities, in order to anticipate human behaviour. Artificial Intelligence enabled smart home devices might speak with one another and collect new data to help in understanding human behaviour. The data is used to predict user behaviour and build situational awareness, or the capacity to understand user preferences and modify parameters as needed.

Smart house or automation technology integrates home appliances with sensors and actuators over the internet, making a home entirely tech-driven with a remote program device. However, the following step will certainly involve Artificial Intelligence, which is rapidly gaining traction in this industry. Light, fan, TV, temperature, entertainment systems, and appliances may all be controlled using the technologies currently available. Lighting control, HVAC, outdoor grass irrigation, kitchen appliances, and security systems are just a few examples of typical uses. At a cost ranging from $174 to $10,000, voice control devices such as Amazon Alexa or Google House have intensified the process of controlling practically every part of the home through the Internet of Things (IoT), which has made tedious daily tasks easier and considerably reduced energy expenses. However, home automation is still mostly limited to a few functions such as locks, security cameras, and occasionally linked appliances, rather than being really intelligent and autonomous.

 

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Alexa, Siri, Google Assistant, and Bixby: The Rise of Digital Assistants

Artificial intelligence is used to operate smart devices via the voice control function of AI-enabled units such as Alexa, Siri, and Google Assistant, in addition to its use in home security systems. Voice commands may also be used to manage advanced home security systems. Researchers are concentrating their efforts on developing new speech recognition technologies that will enhance the use of voice control devices. Hands-free channel surfing and management of Bluetooth speakers are now possible thanks to recent improvements in home automation systems. The rise of voice assistants creates security issues since some researchers have successfully hacked smart devices using inaudible methods.

 

Analyze Potential Home Security Issues Proactively using Artificial Intelligence (AI)

AI-powered computers can swiftly recognise objects or faces using the pattern/face recognition capability. Face recognition software can swiftly scan and compare facial characteristics such as cheekbones, eyes, and chin to current data. Furthermore, these devices may provide notifications to the homeowner’s smartphone regarding visitors at the front door. Modern home security cameras are capable of recognising the faces of family members, friends, and pets.

Artificial intelligence can help next-generation home security systems continually monitor and assess potential security threats. Artificial intelligence logic is encoded into these devices, enabling for the establishment of a customised set of countermeasures to protect the house. Smart cameras with AI are set to play a significant part in home security. These cameras are capable of recording high-definition movies and storing them in the cloud for subsequent viewing. To defend against security issues, an individual can have a good view of his or her home utilising smart connected applications.

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Benefits of Smart Home technology:
Everything Can Be Managed from One Place

A smart home allows you to manage everything in your home from a single device. In certain circumstances, you may just need to install one app to turn on your security camera, air conditioners, television, and other gadgets. As a result, the learning curve will be manageable for you. Furthermore, you will be able to savour the peak of pleasure all at once!

 

Unrivaled adaptability

Smart home technologies, believe it or not, are rather adaptable when it comes to adopting new equipment. Whether you’re buying something new or replacing an old piece of equipment, connecting it with the system will be simple. As a result, being able to integrate these arrivals together will make a homeowner’s task much easier. You won’t have to second-guess yourself when it comes to purchasing new items.

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Energy Efficiency Improvements

It will also be feasible to make everything much more energy-efficient if you consider how you use your smart home equipment. These apps, for example, will provide you with exact control over your home’s cooling and heating systems. As a result, it will be easy for you to lower them as needed to save energy use. Furthermore, even if you forget to turn off lights or other appliances in your home, you may do it even while traveling!

 

Boost Your Home Security

Integrating your surveillance features with smart home technologies may significantly improve the overall security of your home. If someone is breaking and entering your house, for example, you will be alerted even if you are far away from the place. Furthermore, notifying the authorities in the event of a perilous scenario in your home will just take one click. Finally, you may select to be alerted of various security warnings and have your home monitored in real-time.

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Excellent Appliance Performance

Finally, smart home technology can help your appliances run more effectively than they did previously. A smart TV, for example, can help you find better channels and content right away. A smart oven, on the other hand, will guarantee that your mutton is cooked to perfection by providing uniform heating. A well-designed home theatre may aid in the organisation of your film and music collections. With a smart home, the possibilities seem limitless. However, in order to make your life simpler, you must understand how to make the most of everything.

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Report: Cryptocurrency Can Potentially Complement Mobile Money Argues Kenyan Banker

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Report: Cryptocurrency Can Potentially Complement Mobile Money Argues Kenyan Banker

The CEO of one of Kenya’s biggest lenders has argued there is a possibility cryptocurrencies will complement mobile money in Africa but first, there is a need to convince regulators of their benefits.

African Regulators’ Stance on Crypto

Cryptocurrencies can potentially complement mobile money in Africa if regulators on the continent are made to change their perceptions of the digital currencies, the boss of one of Kenya’s biggest lenders has said. According to James Mwangi, CEO of Equity Group Holdings Plc, central banks first need to be convinced of the benefits of cryptocurrencies.

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In remarks published by Bloomberg, Mwangi noted that most of the continent’s central banks have either banned the use of cryptocurrency like bitcoin or have imposed restrictions on its use. He noted, however, that a few countries have or are exploring ways to embrace cryptocurrencies.

According to Mwangi, adopting cryptocurrencies is also one way Africa can get ahead of other continents as far as embracing fourth industrial technologies is concerned.

“Africa will benefit substantially from leapfrogging on the fourth industrial technologies, and cryptocurrency is one of them,” Mwangi is quoted explaining.

Embracing Emerging Technologies

The support his argument, the CEO used the growth of mobile money transactions in Kenya as an example. According to Mwangi, mobile money transactions have since grown to a point where they now outpace hard currency transactions because Kenyan regulators were willing to try out new technology.

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Mwangi also suggested that using emerging technologies like artificial intelligence could be the basis for the continent’s leapfrogging into the fourth industrial revolution.

What are your thoughts on this story? Tell us what you think in the comments section below.

Terence Zimwara

Terence Zimwara is a Zimbabwe award-winning journalist, author and writer. He has written extensively about the economic troubles of some African countries as well as how digital currencies can provide Africans with an escape route.

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Disclaimer: This article is for informational purposes only. It is not a direct offer or solicitation of an offer to buy or sell, or a recommendation or endorsement of any products, services, or companies. Bitcoin.com does not provide investment, tax, legal, or accounting advice. Neither the company nor the author is responsible, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with the use of or reliance on any content, goods or services mentioned in this article.

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Making The Impossible Possible In Film Production With AI

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Making The Impossible Possible In Film Production With AI

Let us have a look at the applications of AI in film production performed by robots and animated.

Artificial intelligence in filmmaking might sound futuristic, but we have reached this place. Technology is already making a significant impact on film production.

Today, most of the outperforming movies that come under the visual effects category are using machine learning and AI for filmmaking. Significant pictures like ‘The Irishman’ and ‘Avengers: Endgame’ are no different.

It won’t be a wonder if the next movie you watch is written by AI, performed by robots, and animated and rendered by a deep learning algorithm.

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But why do we need artificial intelligence in filmmaking? In the fast-moving world, everything has relied on technology. Integrating artificial intelligence and subsequent technologies in film production will help create movies faster and obtain more income. Besides, employing technology will also ease almost every task in film industry.

 

Let us have a look at the applications of AI in film production
Writing scripts

‘Artificial intelligence writes a story is what happens here. Humans can imagine and script amazing stories, but they can’t assure that they will perform well in the theatres. Fortunately, AI can. Machine learning algorithms are fed with large amounts of movie data, which analyses them and comes up with unique scripts that the audience love.

 

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Simplifying pre-production

Pre-production is an important but stressful task. However, AI can help streamline the process involved in pre-production. AI can plan schedules according to actor’s and others’ timing, and find apt locations that will go well with the storyline.

 

Character making

Graphics and visual effects never fail to steal people’s heart. Digital domain applied machine learning technologies are used to design amazing fictional characters like Thanos of Avengers: Infinity War.

 

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Subtitle creation

Global media publishing companies have to make their content suitable for viewers from different regions to consume it. In order to deliver video content with multiple language subtitles, production houses can use AI-based technologies like Natural language generation and natural language processing.

 

Movie Promotion

To confirm that the movie is a box-office success, AI can be leveraged in the promotion process. AI algorithm can be used to evaluate the viewer base, the excitement surrounding the movie, and the popularity of the actors around the world.

 

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Movie editing

In editing feature-length movies, AI supports the film editors. With facial recognition technology, an AI algorithms can recognize the key characters and sort certain scenes for human editors. By getting the first draft done quickly, editors can focus on scenes featuring the main plot of the script.

 

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