Analysis of Research article introduction in the light of Swales’MOVES model

                     

 

Move 1: Establishing a territory
Step 3: Reviewing Items Of Previous Research	This article originally ran as an introduction to the Mobile (digital radiography) DR comparison chart in Nov/Dec 2019 issue.
Step 2: Making Topic Generalizations and/or	As medical imaging technology continues to advance the evolution of digital radiography or X-ray has increasingly moved the modality into the mobile space.
Step 1: Claiming Centrality and/or	X-ray machines are used as an imaging test that’s been used for decades. This can help them diagnose, monitor and threat many medical conditions.

 

Laserson J. researched on this topic in Oct, 2019. Siemens Healthineers earned FDA clearance in 2019 for the Mobilett Elara Max mobile X-ray system. Laserson’s aim of writing this article was to advance in mobile DR technology. DR is one of the most commonly used modalities in the world, with applications from emergency departments to orthopedic clinics.

 

 

 

Move 2: Establishing a niche
Step 1a: Counter-claiming or	By putting digital X rays capability onto a mobile cart-based system, providers are able to conduct imaging anywhere, even at patient’s bedside.
Step 1b: Indicating a gap or	When a patient X-rays is taken, the minutes and hours it take to process and interpret the image can impact the outcome in either direction , AI gives us an opportunity to speed up diagnosis and change the way.
Step 1c: Question-raising or
Step 1d: Continuing a tradition	Discussion about prior researches and approaches adapted in the domain by different researchers and theorists are expanded and referred to.
Step 2: Adding towhat is known	The most significant improvements on the Mobilett Elara Max compared to previous Siemens are focused on enhancing information security.

 

The following is a roundup of recent developments in the mobile DR space:-

 

1: GE brings AI to mobile X-rays. AI gives us an opportunity to speed up diagnosis and change the way we care for patients, which could ultimately save lives and improve outcomes. The chest X-rays AI network was trained using millions of images to identify more than 40 common clinical findings.

 

2: First U.S install of Mobilett Elara Max. The system’s ergonomic design has an autimicrobial coating and fully integrated cables for an unobstructed front view that allows for safe maneuverability.

 

 

 

Move 3: Occupying the niche
Step 1a: Outlining purposes or	Advancement in technology gives us an opportunity to speed up diagnosis and improve outcomes.
Step 1b: Announcing present research	Recent developments in mobile DR :- AI to mobile X rays and Mobilett Elara Max
Step 2: Announcing principal findings	A feature where machines learn to perform tasks, rather than
	simply carrying out computations that are input by human users.Early applications of AI included machines that could play games such as checkers and chess, and programs that could reproduce language. An approach to AI in which a computer algorithm (a set of rules and procedures) is developed to analyze and make predictions from data that is fed into the system. AI is integrated into numerous technologies that people use every day. Machine learning-based technologies are routinely used every day, such as personalized news feeds and traffic prediction maps.
Step 3: Indicating Research article structure	In this section the X-rays machines and their advancement is described. For several years mobile X rays machines has been used routinely for imaging patients too unwell to be transported to the radiology department.

 

 

Conclusion:

Mobile X rays machine may be used outside hospital. There seems to be potential benefits to both patients and health care staff. Further studies are needed to assess the feasibility of use in fragile patients, also regarding staff, relatives and societal consequences and therefore the topic mobile X rays needs more research.

 

MOVES ANALYSIS IS CARRIED OUT ON THE FOLLOWING ARTICLE:

 

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