The Future of Healthcare and AI

Suri, Abhinav

doi:10.1007/978-1-4842-7780-5_7

Cited by 3 publications

(3 citation statements)

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“…However, a study revealed that while VisualDx is a valuable tool, its diagnostic accuracy did not significantly improve in SOC patients, underscoring the need for further development in AI programs tailored to diverse skin tones 22 . DermAssist , a Google Health AI program, offers a similar service, but its effectiveness is yet to be fully evaluated, and concerns exist regarding the diversity of its dataset 54 …”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence in dermatology: advancements and challenges in skin of color

Fliorent,

Fardman,

Podwojniak

et al. 2024

Int J Dermatology

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Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human‐like problem‐solving and decision‐making. AI programs have recently acquired widespread popularity in the field of dermatology through the application of online tools in the assessment, diagnosis, and treatment of skin conditions. A literature review was conducted using PubMed and Google Scholar analyzing recent literature (from the last 10 years through October 2023) to evaluate current AI programs in use for dermatologic purposes, identifying challenges in this technology when applied to skin of color (SOC), and proposing future steps to enhance the role of AI in dermatologic practice. Challenges surrounding AI and its application to SOC stem from the underrepresentation of SOC in datasets and issues with image quality and standardization. With these existing issues, current AI programs inevitably do worse at identifying lesions in SOC. Additionally, only 30% of the programs identified in this review had data reported on their use in dermatology, specifically in SOC. Significant development of these applications is required for the accurate depiction of darker skin tone images in datasets. More research is warranted in the future to better understand the efficacy of AI in aiding diagnosis and treatment options for SOC patients.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence in dermatology: advancements and challenges in skin of color

Fliorent,

Fardman,

Podwojniak

et al. 2024

Int J Dermatology

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“…Thus, technology is enabling the government to resolve the crisis in front of society this efficiently. AI can make healthcare services more accessible and improve efficiency through a quick preliminary diagnosis of patients (Suri, 2021). AI-enhanced governance during the management of the COVID-19 pandemic in several ways which included: Data Analysis and Insights: AI helped governments collect, analyse, and interpret data on the spread of COVID-19 virus.…”

Section: Application Of Ai In Covid-19 Management Andcreation Of Publ...mentioning

confidence: 99%

Public Value-creation Through Application of Artificial Intelligence (AI) in COVID-19 Management: Policy Lessons from India

Katekar,

Cheruku

2023

Indian Journal of Public Administration

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The COVID-19 pandemic had posed significant challenges for public health systems worldwide. Countries had been experimenting with innovative solutions to address the crisis. Artificial Intelligence (AI) has emerged as a promising technology in this regard, with its potential to improve disease detection, contact tracing, and vaccine distribution. The Government of India had administered more than 1,000 million vaccines in a short period since the outbreak of COVID-19, that is, in March 2020. The government harnessed the potential of AI for providing services to citizens during this uncertain time. This article aims to explore the potential of AI in creating public value in the context of COVID-19 management in India. The analysis is based on primary and secondary sources such as research articles, reports published by government and non-government organisations, online databases, and discussion papers. The findings of the study suggest that AI played a critical role in enhancing the effectiveness of COVID-19 management in India. The application of AI has led to significant improvements in disease surveillance, diagnosis, and treatment, thereby creating public value. The study highlights that the assimilation of AI-enabled services increases the citizens’ participation and overall satisfaction and enhances public trust in the government initiatives. The study recommends for a supportive policy environment which fosters innovation and collaboration between stakeholders in leveraging AI. The study also highlights the need for a robust regulatory framework which ensures data privacy and security.

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“…AI is used by biotech businesses such as BERG and pharmaceutical companies such as Takeda in biomarker identification and medication development [21,22]. Google and Apple are other companies investing in AI-powered wearables that measure health and lifestyle [23]. Another example is The Preventive Health feature on Facebook, which connects people to health resources and checkup suggestions [24].…”

Section: Introductionmentioning

confidence: 99%

Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare

2024

OA J Applied Sci Technol

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The twenty-first century has witnessed significant advancements in informatics, reshaping our understanding of data processing and accessibility. Artificial intelligence (AI), encompassing techniques such as machine learning (ML), deep learning (DP), and neural networks (NN), is poised to revolutionize medicine. AI holds the capability of analyzing vast amounts of data, extracting meaningful insights, and making accurate predictions, thereby empowering industries to make informed decisions, drive innovation, and enhance efficiency. The landscape of medical AI has evolved significantly, demonstrating expert-level disease detection from medical images and promising breakthroughs across various industries. AI revolutionizes medical practice by leveraging advanced algorithms and machine learning capabilities to improve diagnostics, treatment planning, and overall patient care. However, the deployment of medical AI systems in regular clinical practice still needs to be tapped, presenting complex ethical, technical, and human-centered challenges that must be addressed for successful implementation. While AI algorithms have shown efficacy in retrospective medical investigations, their translation into practical medical settings has been limited, raising concerns about their usability and interaction with healthcare professionals. Moreover, the representativeness of retrospective datasets in real-world medical practice is subject to filtering and cleaning biases. Integrating AI into clinical medicine holds great promise for transforming healthcare delivery, improving patient care, and revolutionizing aspects such as diagnosis, treatment planning, drug discovery, personalized treatment, and medical imaging. With advanced algorithms and machine learning capabilities, AI and robotics in Healthcare can analyze large volumes of medical data, extract meaningful insights, and provide accurate predictions, empowering healthcare professionals to make informed decisions and optimize resource allocation. The availability of extensive clinical, genomics, and digital imaging data, coupled with investments from healthcare institutions and technology giants, underscores the potential of AI in healthcare. This review article explores AI's powerful potential to revolutionize healthcare delivery across multiple domains, emphasizing the need to overcome challenges and harness its transformative capabilities in clinical practice.

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The Future of Healthcare and AI

Cited by 3 publications

References 0 publications

Artificial intelligence in dermatology: advancements and challenges in skin of color

Artificial intelligence in dermatology: advancements and challenges in skin of color

Public Value-creation Through Application of Artificial Intelligence (AI) in COVID-19 Management: Policy Lessons from India

Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare

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