AI in Surgery

Omiye, Jesutofunmi A.; Swaminathan, Akshay; Ross, Elsie Gyang

doi:10.1002/9781119790686.ch28

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…Atomwise [123,124], BenevolentAI [125], Insilico Medicine [126] Diagnostics and imaging Analysis of medical images, such as X-rays, MRIs, or CT scans and faster speed and accuracy of detection of abnormalities than human specialists. Aidoc [127,128], Zebra Medical Vision [129],…”

Section: Drug Discoverymentioning

confidence: 99%

Innovative Robotic Technologies and Artificial Intelligence in Pharmacy and Medicine: Paving the Way for the Future of Health Care—A Review

Stasevych,

Zvarych

2023

BDCC

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The future of innovative robotic technologies and artificial intelligence (AI) in pharmacy and medicine is promising, with the potential to revolutionize various aspects of health care. These advances aim to increase efficiency, improve patient outcomes, and reduce costs while addressing pressing challenges such as personalized medicine and the need for more effective therapies. This review examines the major advances in robotics and AI in the pharmaceutical and medical fields, analyzing the advantages, obstacles, and potential implications for future health care. In addition, prominent organizations and research institutions leading the way in these technological advancements are highlighted, showcasing their pioneering efforts in creating and utilizing state-of-the-art robotic solutions in pharmacy and medicine. By thoroughly analyzing the current state of robotic technologies in health care and exploring the possibilities for further progress, this work aims to provide readers with a comprehensive understanding of the transformative power of robotics and AI in the evolution of the healthcare sector. Striking a balance between embracing technology and preserving the human touch, investing in R&D, and establishing regulatory frameworks within ethical guidelines will shape a future for robotics and AI systems. The future of pharmacy and medicine is in the seamless integration of robotics and AI systems to benefit patients and healthcare providers.

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Section: Drug Discoverymentioning

confidence: 99%

Innovative Robotic Technologies and Artificial Intelligence in Pharmacy and Medicine: Paving the Way for the Future of Health Care—A Review

Stasevych,

Zvarych

2023

BDCC

View full text Add to dashboard Cite

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“…For instance, if the training data skews the representativeness of one demographic group versus another, LLM-based suggestions in telehealth could lead to or exacerbate gender, racial, or ethnic inequities. This concern is not merely theoretical; commercially accessible LLMs have exhibited racial and gender biases in non-medical contexts, and these very models have been found to propagate stereotypes related to race within the field of medicine [23]. Biases may also arise from LLMs learning stigmatizing representations of language in training data [153], and propagating those through inappropriate language or portraying mental health issues in a negative light.…”

Section: Potential Harmsmentioning

confidence: 99%

“…Several mental healthcare organizations and companies [18][19][20] have also begun to research the integration of LLMs into the design of their services. This increased use of LLMs in service delivery has been met with excitement [21], but also with justified skepticism, given potential racial or gender biases [22,23] and unexpected outputs [24] from LLM-based chatbots. For example, in June 2023, the National Eating Disorder Association was forced to shut down a chatbot created to provide clinically validated information after the chatbot provided harmful and dangerous advice to users, including diet and weight loss advice [24,25].…”

Section: Introductionmentioning

confidence: 99%

Benefits and Harms of Large Language Models in Digital Mental Health

De Choudhury,

Pendse,

Kumar

2023

Preprint

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The past decade has been transformative for mental health research and practice. The ability to harness large repositories of data, whether from electronic health records (EHR), mobile devices, or social media, has revealed a potential for valuable insights into patient experiences, promising early, proactive interventions, as well as personalized treatment plans. Recent developments in generative artificial intelligence, particularly large language models (LLMs), show promise in leading digital mental health to uncharted territory. Patients are arriving at doctors' appointments with information sourced from chatbots, state-of-the-art LLMs are being incorporated in medical software and EHR systems, and chatbots from an ever-increasing number of startups promise to serve as AI companions, friends, and partners. This article presents contemporary perspectives on the opportunities and risks posed by LLMs in the design, development, and implementation of digital mental health tools. We adopt an ecological framework and draw on the affordances offered by LLMs to discuss four application areas---care-seeking behaviors from individuals in need of care, community care provision, institutional and medical care provision, and larger care ecologies at the societal level. We engage in a thoughtful consideration of whether and how LLM-based technologies could or should be employed for enhancing mental health. The benefits and harms our article surfaces could serve to help shape future research, advocacy, and regulatory efforts focused on creating more responsible, user-friendly, equitable, and secure LLM-based tools for mental health treatment and intervention.

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“…This paper sets out on an excursion to investigate the sweeping effect of LLMs on the medical care scene. We want to explain how these models are reclassifying the eventual fate of medication and to address the moral contemplations that go with this groundbreaking innovation [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

The Future of Medicine: Large Language Models Redefining Healthcare Dynamics

Haque,

Chowdhury

2023

Preprint

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<p>The medical care industry is on the cusp of an extraordinary period, with large language models (LLMs) arising as incredible assets for reclassifying medical care elements. This paper investigates the potential and effect of LLMs in different parts of medication, including diagnostics, patient consideration, drug revelation, and medical services organization. It dives into the open doors and difficulties introduced by LLMs, accentuating the moral contemplations and the requirement for capable reception. By looking at late turns of events and contextual investigations, this paper offers a brief look into the developing scene of medical services, where LLMs are ready to assume a focal part in reshaping the eventual fate of medication.</p>

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AI in Surgery

Cited by 3 publications

References 5 publications

Innovative Robotic Technologies and Artificial Intelligence in Pharmacy and Medicine: Paving the Way for the Future of Health Care—A Review

Innovative Robotic Technologies and Artificial Intelligence in Pharmacy and Medicine: Paving the Way for the Future of Health Care—A Review

Benefits and Harms of Large Language Models in Digital Mental Health

The Future of Medicine: Large Language Models Redefining Healthcare Dynamics

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