Artificial Intelligence in Radiology

ARTIFICIAL INTELLIGENCE IN RADIOLOGY
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Table of Contents 1.    Introduction. 3 2.    Literature Review.. 4 3.    Case Description of the use of AI in Radiology by Urbanside Hospital 8 3.1 Outcome of the Research. 9 4.    Analysis and Discussion. 9 4.1      Ethical Perspective. 9 4.2 Governance Mechanisms. 11 4.3      Regulatory Stance. 11 5.    Reflections. 12 6.    References. 15  List of Figures Figure 1: Critical Factors Concerning Digital Technology in Medicine. 5 Figure 2: Image Analysis through AI in Radiology in 2023(Predictive) 13
Artificial Intelligence In Radiology
1 Introduction
Since the application of technology transformed the way business is conducted, the healthcare sector has also been changed with the latest technological tools. Artificial intelligence (AI), one of the advanced forms of technological revolution, has also modified the radiology department in hospitals. AI in radiology departments of many major hospitals in the USA has blessed the healthcare sector with multiple benefits compared with conventional radiology tools (Loria). The rush of radiology films and the more accurate imaging through AI and other digital tools in radiology are some of the prime positive outcomes in this regard.
Governance and ethics must be prioritized while incorporating AI in radiology (Schiff et al., 2020). Informed consent of the patients, data protection, and bias must be handled with vigilance and governed appropriately for employing AI in radiology. While testing and examining for future concerns, ethical concerns regarding data protection can be developed, which may disrupt the trust engagements between the patients and the medical specialists.
This assessment will focus on the research and analysis of the usage of AI in the radiology sections of different hospitals in the USA. Also, there would be an examination of the ethics and governance associated with incorporating digital systems in radiology.
2 Literature Review
Considering the increasing indulgence of digital systems in many legal, social, and economic sectors, the new technological changes have also affected the healthcare sector. Many new digital transformational tools have been incorporated into healthcare (Stark et al. 2018). AI is one of the most commonly used technological tools in the healthcare sector. The usage of AI in the healthcare industry has certainly provided many benefits.
* The ultimate benefit of the indulgence of AI in healthcare is the reduced time and money in scanning, analysing, and examining patients. These novice modifications have allowed the sector to utilize the time and money for further research and development of the whole industry.
* Another prominent well-being of digital technology is the extensive availability of data and the rapid development of big data. These development features through AI have provided room to the health sector for future research.
* Deep learning feature through Machine learning (ML) and AI has enabled healthcare physicians to predict the health conditions of patients based on algorithms.
Even though programmatic technology has revolutionized the medical field, it has created several critical issues like low cognitive trust and data privacy (Rey & Bouaynaya 2022). There are still some gaps in digital technology development, disrupting the overall progress of medicine. As discussed in the figure below, the subjectivity of data collection methods has also carved out some questionable comments regarding the authenticity and trust of virtual transformations in healthcare.
left34861500Figure SEQ Figure \* ARABIC 1: Critical Factors Concerning Digital Technology in Medicine
* The neural network has been mainly applied in radiology but not in other sectors like clinics.
* Hesitation and data privacy concerns have uniformly hindered the application of artificial intelligence in all medical sectors.
* The continuous refusal also has limited oncologists’ adaptation of robotics language in all healthcare departments. The radiologists and the oncologists are considered the prime users and beneficiaries of ML and AI; their refusal certainly reduces the temptation in other departments.
Although AI and ML have many potential benefits, their adaptation and popularity are linked with medical practitioners, especially radiology specialists (Buck et al. 2021). Without popularizing these widespread techniques, other fields of medicine cannot be benefited from them.
The neural network can be helpful in many other healthcare sectors besides radiology. For example, depression is a recurring disease that is becoming prevalent. In some cases, the severity of depression can cause severe health disorders in patients. This deadly disease can be detected beforehand by evaluating its early symptoms using elite technological tools. The usage of AI can help in the diagnosis of depression by evaluating the symptoms. It is evident from the facts that the increased data privacy concerns can result in an increased depression ratio among patients (Yan & David 2021). One ultimate negative factor associated with AI is the extreme privacy concerns of patients’ data.
The data privacy and trust issues can be sorted by addressing patient concerns. Since AI can cure depression patients, the patients should be motivated to share their information to help the health practicians make cognitive decisions. If the patients trust the healthcare sector, they will undoubtedly share their personal healthcare information (PHI) for their treatment. Established governments can also play a productive role in developing patient trust factors. For example, the government can develop regulations and strict checks on data protection and privacy concerns. Such regulations will maintain the ethics connected with patients’ data security, and they will be able to share their information.
The digitalization of the healthcare information system has developed a communication network of physicists and patients. The channel information system enables the patients and the doctors to interact with each other and cure diseases in time. Many online healthcare websites facilitate doctors and patients to interact to cure certain diseases. The doctors can attend to their patients using different mediums online like video conferencing and skype. Patients can communicate and book appointments with their doctors using online or offline communication mediums (Zhao & Tang 2021). These interactive websites and online tools have certainly enhanced the capacity of medical practitioners and improved the quality-of-service delivery for patients with no human errors.
The outbreak of COVID-19 transformed the working mechanisms and tactics of every sector in the world. Virtual dependence got increased massively during the pandemic period. The initiation of the mobile contact tracing application (CTA) for tracing COVID-19 traces by the German government proved as a landmark in the genre of technology. With this application, COVID-19 patients could save the data and information regarding their positive or negative COVID-19 test to keep others informed in their contact. The prime function of the German CTA application was to save the information and transmit it to others in contact with each other (Reith et al. 2021). Apart from being hyperactive, this approach has helped the German government diffuse COVID-19.
The healthcare industry has faced several issues in adopting and sustaining new technological tools. The patient and healthcare can be improved by maintaining electronic health records (EHR), which are under discussion in many major US hospitals. Such records can help reduce the trace of patient history and improve the service delivery of the healthcare sector. Multiple issues like lack of funding and government support to sustain such elite technological features have disrupted the smooth working of the different healthcare sections in the USA. The sharing of healthcare information through EHR reduces the patient’s referral time, duplication of tests, and admission time (Srivastava et al. 2021). Sustained government support, coupled with sound knowledge of the efficacy of digital technology in the healthcare sector, can help improve service delivery to patients.
Electronic patient records maintenance can help patients quickly shift from one medical centre to another to treat their diseases (Ambinder, 2005). Also, electronic data accession will enable all the health centers to easily access the patient’s data, saving the money and time of both hospitals and patients.
3 Case Description of the use of AI in Radiology by Urbanside Hospital
Technology has made its way to every sector to transform its working mechanisms and reduce human errors. To reduce human errors and the daily burden of work, the likelihood of implementing artificial intelligence was examined in a major US hospital, i.e., Urbanside. The prime aim of this research at Urbanside was to detect the efficacy of digital technology in routine medical tasks and to sustain perfection in medicine. Considering the rush area and the burden of daily patients in the radiology department of this tertiary healthcare hospital at the Urbanside US hospital, implementing the elite technological tool was imminent.
Similarly, the recent developments in digital technology have enhanced human capacities in every field. Doctors, oncologists, and radiologists can now make precise decisions based on algorithm-stated patient predictive reports using artificial intelligence. Human errors are eternal; thus, many organizations have begun to opt for the latest technological tools to optimize their working capacities and qualities. Though AI and other associated tec...