AI Solutions to Public Health Issues

Santosh, K. C.; Gaur, Loveleen

doi:10.1007/978-981-16-6768-8_3

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…Many challenges occur in the diagnosis, such as late symptom onset, inconsistent symptoms, and lack of molecular markers. AI tools such as K-nearest neighbor (KNN), artificial neural network (ANN), and support vector machine (SVM) are studied to identify subtle abnormal imaging findings that aid in the early detection of pancreatic cancer [ 15 ]. The AI-powered ML algorithm was used to predict the probability of developing lung cancer after initial screening with the low-dose CT scan.…”

Section: Reviewmentioning

confidence: 99%

Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine

Iqbal,

Cortés Jaimes,

Makineni

et al. 2023

Cureus

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Artificial intelligence (AI) has opened new medical avenues and revolutionized diagnostic and therapeutic practices, allowing healthcare providers to overcome significant challenges associated with cost, disease management, accessibility, and treatment optimization. Prominent AI technologies such as machine learning (ML) and deep learning (DL) have immensely influenced diagnostics, patient monitoring, novel pharmaceutical discoveries, drug development, and telemedicine. Significant innovations and improvements in disease identification and early intervention have been made using AI-generated algorithms for clinical decision support systems and disease prediction models. AI has remarkably impacted clinical drug trials by amplifying research into drug efficacy, adverse events, and candidate molecular design. AI’s precision and analysis regarding patients’ genetic, environmental, and lifestyle factors have led to individualized treatment strategies. During the COVID-19 pandemic, AI-assisted telemedicine set a precedent for remote healthcare delivery and patient follow-up. Moreover, AI-generated applications and wearable devices have allowed ambulatory monitoring of vital signs. However, apart from being immensely transformative, AI’s contribution to healthcare is subject to ethical and regulatory concerns. AI-backed data protection and algorithm transparency should be strictly adherent to ethical principles. Vigorous governance frameworks should be in place before incorporating AI in mental health interventions through AI-operated chatbots, medical education enhancements, and virtual reality-based training. The role of AI in medical decision-making has certain limitations, necessitating the importance of hands-on experience. Therefore, reaching an optimal balance between AI’s capabilities and ethical considerations to ensure impartial and neutral performance in healthcare applications is crucial. This narrative review focuses on AI’s impact on healthcare and the importance of ethical and balanced incorporation to make use of its full potential.

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Section: Reviewmentioning

confidence: 99%

Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine

Iqbal,

Cortés Jaimes,

Makineni

et al. 2023

Cureus

View full text Add to dashboard Cite

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“…Aung, Wong, and Ting (2021, p. 5) noted that the application of AI systems in the medical field dates to the year 1976 when an algorithm was first employed in identifying the causes of acute abdominal pain. Today, the use of artificial intelligence in healthcare is helping to ease administrative burden on physicians by performing less sophisticated and more routine tasks such as booking appointments and managing communications with patients and even in some sophisticated and less routine tasks such as the detection of diseases including cancer, the detection of sources of pain, chest X-ray analyses, medical imaging and the identification of brain tumors, among others (Santosh & Gaur, 2021, p. 25). In making the case for the benefits of adopting algorithms for complex and high-uncertainty tasks, the use of algorithms in the medical field is an example of the applicability of these systems in relieving administrative burden from medical professionals to whom this type of burden is rather common (Javanmardian & Lingampally, 2018).…”

Section: Advantages Of Service Algorithms For High Complexity High Un...mentioning

confidence: 99%

Artificial intelligence, task complexity and uncertainty: analyzing the advantages and disadvantages of using algorithms in public service delivery under public administration theories

Nzobonimpa

2023

DTS

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PurposeThis article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.Design/methodology/approachThe author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.FindingsAfter presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.Research limitations/implicationsAs a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.Practical implicationsThe paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.Social implicationsThe paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.Originality/valueThis research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.

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Development of Digital Capabilities in Small Business: A Necessary Condition Analysis

Dávila,

Sayán,

Guillen

et al. 2023

Studies in Systems, Decision and Control

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AI Solutions to Public Health Issues

Cited by 8 publications

References 26 publications

Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine

Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine

Artificial intelligence, task complexity and uncertainty: analyzing the advantages and disadvantages of using algorithms in public service delivery under public administration theories

Development of Digital Capabilities in Small Business: A Necessary Condition Analysis

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