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Comparative Evaluation of Effectiveness of Standard of Care Alone and in Combination With Homoeopathic Treatment in COVID-19–Related Rhino-Orbito-Cerebral Mucormycosis (ROCM): Protocol for a Single Blind, Randomized Controlled Trial

Comparative Evaluation of Effectiveness of Standard of Care Alone and in Combination With Homoeopathic Treatment in COVID-19–Related Rhino-Orbito-Cerebral Mucormycosis (ROCM): Protocol for a Single Blind, Randomized Controlled Trial

The authors consider it their ethical responsibility to share this reviewed protocol with the professional community as a resource for further research applicable to mucormycosis cases not specifically linked to COVID-19 infection. This initiative aims to ensure preparedness with evidence, regardless of its availability if similar emergencies arise in the future. Thus, we present this protocol to the community in hopes it would be used for immunocompromised or diabetes-related mucormycosis in individuals.

Harleen Kaur, Jyoti Sachdeva, Ramesh Bawaskar, Twinkle Goyal

JMIR Res Protoc 2025;14:e57905

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The Dual Nature of AI in Information Dissemination: Ethical Considerations

The Dual Nature of AI in Information Dissemination: Ethical Considerations

To address these ethical challenges, it is crucial to examine the dimensions that AI introduces into the discourse on misinformation. Key aspects such as transparency, content regulation, and fostering information literacy are essential to understanding AI’s ethical role in shaping the dissemination of information.

Federico Germani, Giovanni Spitale, Nikola Biller-Andorno

JMIR AI 2024;3:e53505

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Regulating AI in Mental Health: Ethics of Care Perspective

Regulating AI in Mental Health: Ethics of Care Perspective

Surprisingly, these aspects are almost entirely absent from recent regulatory and ethical guidance and debate. This article argues that the responsible AI approach—which is the dominant ethics approach ruling most regulatory and ethical guidance—is insufficient because it does not refer to AI’s impact on human relationships. This reinforces a narrow concept of accountability and responsibility of companies developing AI.

Tamar Tavory

JMIR Ment Health 2024;11:e58493

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Research Into Digital Health Intervention for Mental Health: 25-Year Retrospective on the Ethical and Legal Challenges

Research Into Digital Health Intervention for Mental Health: 25-Year Retrospective on the Ethical and Legal Challenges

We have observed that research teams designing and delivering evaluations frequently invest substantial effort in deliberating on ethical and legal challenges around DMHIs. Conducting our own evaluations ethically and legally has been one of our primary concerns.

Charlotte L Hall, Aislinn D Gómez Bergin, Stefan Rennick-Egglestone

J Med Internet Res 2024;26:e58939

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The Opportunities and Risks of Large Language Models in Mental Health

The Opportunities and Risks of Large Language Models in Mental Health

LLMs will similarly do harm if they are not designed and implemented in consideration of and are not consistent with relevant ethical principles and standards when operating in the domain of mental health. Core ethical principles in the health care context include beneficence, nonmaleficence, justice, and autonomy [61].

Hannah R Lawrence, Renee A Schneider, Susan B Rubin, Maja J Matarić, Daniel J McDuff, Megan Jones Bell

JMIR Ment Health 2024;11:e59479

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Data-Driven Fundraising: Strategic Plan for Medical Education

Data-Driven Fundraising: Strategic Plan for Medical Education

Ethics in higher education fundraising are about conducting fundraising efforts in a manner that is consistent with ethical values and principles and that fosters trust and accountability.

Alireza Jalali, Jacline Nyman, Ouida Loeffelholz, Chantelle Courtney

JMIR Med Educ 2024;10:e53624

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Human-AI Teaming in Critical Care: A Comparative Analysis of Data Scientists’ and Clinicians’ Perspectives on AI Augmentation and Automation

Human-AI Teaming in Critical Care: A Comparative Analysis of Data Scientists’ and Clinicians’ Perspectives on AI Augmentation and Automation

Furthermore, 92% of experts agreed that there were no social or ethical concerns and that this task should be augmented by AI (level 3). In the first round, 81.8% of data science experts agreed that this task could be augmented by AI but would always require humans in the lead (level 2). This opinion increased to 90.1% in rounds 2 and 3.

Nadine Bienefeld, Emanuela Keller, Gudela Grote

J Med Internet Res 2024;26:e50130

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Article has an altmetric score of 9