Mediaboss Marketing

Hui Xie,1,2 Qing Li,2,3 Ping-Feng Hu,4 Sen-Hua Zhu,5 Jian-Fang Zhang,6 Hong-Da Zhou,1 Hai-Bo Zhou4

1Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Peoples Republic of China; 2Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province, Chenzhou, 423000, Peoples Republic of China; 3Department of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Peoples Republic of China; 4Department of Radiology, The Second Peoples Hospital of Chenzhou City, Chenzhou, 423000, Peoples Republic of China; 5Beijing Linking Medical Technology Co., Ltd, Beijing, 100085, Peoples Republic of China; 6Department of Physical Examination, Disease Control and Prevention of Chenzhou, Chenzhou, 423000, Peoples Republic of China

Correspondence: Qing LiDepartment of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, 25 Renmin Street, Chenzhou, 423000, Peoples Republic of ChinaTel +86 19918761912Email xnxyliqing@163.com

Objective: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19.Methods: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.001. Finally, 39 cases (29 positive and 10 negative) were selected for the comparative test. Experimental group: an attending physician a and an associate chief physician a read the CT images to diagnose COVID-19 with the help of the AI system. Control group: an attending physician b and an associate chief physician b did the diagnosis only by their experience, without the help of the AI system. The time spent by each doctor in the diagnosis and their diagnostic results were recorded. Paired t-test, univariate ANOVA, chi-squared test, receiver operating characteristic curves, and logistic regression analysis were used for the statistical analysis.Results: There was statistical significance in the time spent in the diagnosis of different groups (P< 0.05). For the group with the optimal diagnostic results, univariate and multivariate analyses both suggested no significant correlation for all variables, and thus it might be the assistance of the AI system, the epidemiological history and other factors that played an important role.Conclusion: The AI system developed by us, which was created due to COVID-19, had certain clinical practicability and was worth popularizing.

Keywords: CT, COVID-19, intelligent analysis, AI, helping role

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Artificial intelligence in helping with COVID-19 | JIR - Dove Medical Press

VERONA, Italy--(BUSINESS WIRE)--Trueblue, after having announced the integration of its Artificial Intelligence Relationship Management with Microsoft Dynamics 365 and Power Platform, officially launches on the market:

AiDEA

Smart Customer Engagement

AiDEA is the new AI driven Omnichannel Customer Engagement suite. The foundation of the solution, represented by Artificial Intelligence , integrates and powers the operational and analytical functionalities based on Microsoft Dynamics 365 and Power Platform, for a holistic and integrated experience, with the goal of revolutionizing the working model of Pharma & Life Science markets, simplifying omni-channel engagement through intuitive and conversational interaction.

Two fundamental components guide the change, whose union had not yet materialized in the reference market: the concrete integration of Big Data in the perspective of Multichannel Management and the use of Artificial Intelligence functionalities and algorithms. The latter is an element that can no longer be postponed from an IT point of view, as it is necessary to drive Customer Engagement processes to satisfy company objectives from both a strategic and an operational point of view.

These elements require a structural change in the approach of organizations and tools, as a generic Customer Relationship Management system is no longer sufficient. It is in fact necessary to adopt specific Smart Omnichannel Customer Engagement solutions, fully enabled in terms of Artificial Intelligence, to have, in a quick, simple and intuitive way, precise indications about one's own customers.

As part of this transition in fact, Pharma companies such as Angelini Pharma, Alfasigma and others are taking this direction with strength and determination with the aim of innovating and achieving their business results faster.

"Artificial Intelligence represents a tremendous opportunity to increase our effectiveness and we want to provide this competitive advantage to our employees thanks to AiDEA" said Pierluigi Antonelli, CEO of Angelini Pharma "After a long and thorough analysis, we identified Trueblue and Microsoft as the best partners to advance our Customer Engagement capabilities by delivering an innovative digital CRM solution that transforms strategy into action.

Trueblue, which has always been at the center of technological and digital innovation for the pharmaceutical industry, thanks to the integration with Microsoft introduces with AiDEA a new paradigm in which Artificial Intelligence is the backbone and key factor of the evolutionary process.

"Through this integration, Trueblue will help companies in the industry accelerate their growth and find new ways to drive Digital Innovation through a wide range of solutions that will enable them to simplify the use of AI in their daily activities," said Marco Bonesini CEO of Trueblue

In todays reality of accelerated digital transformation processes, pharma & life science companies rely on proactive solutions such as AIDEA, integrated with Dynamics 365 and Power Platform, to enable effective omnichannel strategies said Elena Bonfiglioli, Managing Director, HealthCare and Life Sciences, EMEA Regional Lead.

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Trueblue Designs the Future of Artificial Intelligence and Analytics for Healthcare With Aidea Integrated With Microsoft Dynamics 365 - Business Wire

NORFOLK, Va. - News 3 is taking action for your health!

March is National Colorectal Cancer Awareness Month. Be aware - the Hampton Roads area was identified as a "hot spot" for colon cancer deaths, according to the American Cancer Society.

In Norfolk, a trial is currently underway, adding the tool of artificial intelligence in the quest for prevention.

As the video indicates, AI technology is like an extra set of eyes; it highlights areas of interest when a patient undergoes a colonoscopy.

Early detection means better outcomes, and the addition of artificial intelligence in the screening appears to be an asset for both doctor and patient.

Dr. David Johnson calls it a game changer.

Weve used it for a year. We find it incredibly helpful in our practice and now in the trial, we see an increment in even among experts detecting polyps. We can do better. There were 3,000 cases in 2020 of colon cancer, 53,000 deaths. Barbara, we have to do better, and we can," Dr. Johnson said.

Related: Local woman shares story of colon cancer, warns others to get screened

The American Cancer Society recommends that you start screening at the age of 45 if you are at normal risk.

If you are at a higher risk, talk to your primary care provider.

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Detecting colon cancer early with artificial intelligence - wtkr.com - wtkr.com

Interactive online platforms have become an integral part of our daily lives. While user-generated content, free from traditional editorial constraints, has spurred vibrant online communications, improved business processes and expanded access to information, it has also raised complex questions regarding how to moderate harmful online content. As the volume of user-generated content continues to grow, it has become increasingly difficult for internet and social media companies to keep pace with the moderation needs of the information posted on their platforms. Content moderation measures supported by artificial intelligence (AI) have emerged as important tools to address this challenge.

Whether you are managing a social media platform or an e-commerce site, minimizing harmful content is critical to the user experience. Such harmful content can include everything from posts promoting violence to child abuse. In fact, the range and scope of potential harmful content has proven too broad for human moderators to comprehensively review. AI systems, designed to mirror the way humans think and process information, may be able to improve the speed and accuracy of this process. AI technology can take large data sets and teach machines to identify patterns or make predictions about certain inputs. Ultimately, this capability allows computers to recognize and filter certain words or images with more efficiency than humans can process this information. As an added benefit, this reduces or could potentially eliminate the need for human moderators to be directly exposed to harmful content.

While AI systems are promising, they are not without their own set of challenges. By some estimates, there are 2.5 quintillion bytes of data created each day. As such, while AI offers a way to more efficiently process large amounts of data, the volume of content at issue is now so vast that it has become critical that AI models perform with both speed and accuracy. And achieving optimal accuracy requires an AI model to not only be based on accurate data and imagery but also be able to appreciate nuances in the content reviewed to distinguish satire from disinformation. Further, questions have been raised regarding whether these models remove the inevitable biases of human content moderators, or if the AI models themselves actually introduce, entrench or amplify biases against certain types of users. One study, for example, found that AI models trained to process hate speech online were 1.5 times more likely to identify tweets as offensive or hateful when written by African-American users.

This tension demonstrates the difficult balance between designing models to address human inefficiencies and root out human error in content moderation while ensuring new systematic issues are not introduced into the models themselves. In fact, U.S. policymakers have conducted numerous hearings and floated legislative proposals to address concerns regarding bias within AI systems and the unintentional discrimination that could result from using such systems.

AI systems undeniably offer online platforms enhanced capabilities to effectively moderate user-generated content, but they present their own set of challenges that must be considered as these systems are designed and deployed as moderation tools.

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Everything in Moderation: Artificial Intelligence and Social Media Content Review - JD Supra

NEW YORK, March 25, 2021 /PRNewswire/ -- Fact.MR's report on global autonomous farm equipment market projects a steady growth of over 10% CAGR through 2021 to reach valuation of US$ 150 Bn by 2031. Penetration of Artificial Intelligence (AI) and advanced technology in farming sector to spike the demand of the market in coming years. Fact.MR's study projects fully and partially autonomous tractors to gain traction by 2031.

The latest edition of autonomous farm equipment market by Fact.MR finds that manufacturers are investing more in R&D activities to capitalize on upcoming opportunities, spurring the sales. Significant development in technology and incorporation of AI in the fully automated tractors and harvesters is attracting the suppliers to invest more in the similar technology to improve the efficiency

With the rising demand of autonomous tractors equipped with auto-steering and auto data collecting systems from the customers, manufacturers are riveted to invest more in R&D activities to incorporate AI. Hence fostering the sales.

"Heightened investments by manufacturers in research and development for advanced technology such as drones and fully automated tractors is stimulating growth of autonomous farm equipment," says a Fact.MR analyst.

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Key Takeaways

Competitive Landscape

Some of the key players profiled by Fact.MR supplying autonomous farm equipment include Bobcat, AGCO Corporation, John Deere, Case IH, Yanmar, D Robotix, Agribotix, ADAMA Agricultural Solution Ltd., Mahindra, Rowbot, and Clearpath Robotics among others. According to the study, the market is highly competitive and quality product innovation is the key strategy adopted by prominent players.

For instance, in December 2020, Raven Industries announced the launch of its first commercially-available Driverless Ag Technology: AutoCart. This autonomous grain cart solution is available in the market since the 2021 harvest season. The new product launch showcased the company's position as the technology leader in the agriculture by bridging the gap from human-operated to fully-autonomous platform.

In similar fashion, Yanmar Agribusiness Co. Ltd., in February 2021, upgraded its autonomous tractor with multi-frequency antenna to improve its performance capabilities. This upgraded autonomous tractors series will be available in the market from 1st April 2021, capable of full or partial autonomous operation, providing customer with the improved results for their farming needs.

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Fact.MR, in its latest report, offers a detailed segmentation of the global autonomous farm equipment market. The study divulges essential insights on the autonomous farm equipment market on the basis of product (tractors, harvesters, UAVs, and others), and region (North America, Latin America, Europe, East Asia, South East Asia & Oceania, and MEA)

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Explore Fact.MR's Coverage on the Automotive Domain

Trailer Terminal Tractor Market: Fact.MR's latest coverage on global trailer terminal tractor market gives a detailed analysis on the prominent growth dynamics, including possible drivers, opportunities and new entrants, expected to prevail across the landscape for the upcoming decade. A detailed insight regarding key geographies and prominent manufacturers has been embedded in this report.

Farm Tires Market: The latest report by Fact.MR on global farm tires market offers an unbiased analysis on the key drivers, trends and opportunities expected to prevail across prominent segments and key geographies for the forthcoming assessment period. Additionally, details about prominent manufacturers and their revenue shares have also been incorporated.

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