Perspectives on Human-AI Interaction Applied to Health and Wellness Management: Between Milestones and Hurdles

Sqalli, Mohammed Tahri; Al-Thani, Dena; Qaraqe, Marwa; Fernández-Luque, Luis

doi:10.1007/978-3-030-67303-1_4

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…The incorporation of machine learning does not mean the substitution of human knowledge, but rather its enhancement. It is difficult to promote cooperation between medical and AI systems while maintaining the provision of patient-centered care (6).…”

Section: Ethical Challenges In Implementationmentioning

confidence: 99%

Navigating the Ethical Landscape: Implementing Machine Learning in Smart Healthcare Informatics

Sharma,

Sharma

2024

Indian J Community Health

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The integration of Machine Learning (ML) into healthcare informatics holds immense promise, revolutionizing patient care and treatment strategies. However, as this technology advances, it brings forth ethical challenges crucial for careful navigation. ML offers unprecedented abilities to analyze vast healthcare data, leading to personalized medicine and improved outcomes. Yet, ethical concerns emerge, notably in privacy protection, algorithm bias, transparency, informed consent, and data quality. Transparency, explainability, and patient autonomy in decision-making processes are crucial to foster trust and accountability. Striking a balance between innovation and compliance, ensuring data quality, and promoting human-AI collaboration are essential. Addressing these challenges demands adherence to ethical frameworks, continuous monitoring, multidisciplinary governance, education, and regulatory compliance. To fully harness ML's potential in healthcare while upholding ethical standards, collaboration among stakeholders is imperative, ensuring patient welfare remains central amid technological advancements. Ethical considerations must be embedded at every stage of ML implementation to maintain an ethical, equitable, and patient-centered healthcare system.

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Section: Ethical Challenges In Implementationmentioning

confidence: 99%

Navigating the Ethical Landscape: Implementing Machine Learning in Smart Healthcare Informatics

Sharma,

Sharma

2024

Indian J Community Health

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“…AI enabled chat bots for depression counseling 3. AI enabled app to connect with experts based on cause of depression Lots of research articles have been written to find out features that may locate depression based on voice and facial features [10]- [12].…”

Section: Ai In Mental Healthmentioning

confidence: 99%

AI Based Assistance To Reduce Suicidal Tendency Among Youngsters

Rawat

Bist

Mulyati³

et al. 2022

ATM

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Suicidal tendency among youngsters is one of emerging issue in society.This not only results in loss of life but also has disruptive psychosocial and adverse socio-economic effects. It accounts for 1.4% of all deaths. It is also reported that men die more than women. If we look at male to female ratio regarding suicide death, then it is 1.5 to 1 and is highest in richest countries. Each year, approximately 800,000 people die by suicide worldwide. Fast life style, academic pressure, relationships, drug addiction etc, are major causes of this. This is exacerbated by the presence of new factors that arise as a result of the COVID-19 outbreak, which puts new pressures on society, which of course worsens the mental condition of today's society.Governments and NGOs are highly concerned about it. In this paper, we are concerned about the role of technology to prevent it. We will discuss how artificial intelligence can help in keeping the wellbeing of the mental state of human beings. Our focus would be on use of artificial intelligence in predicting and preventing suicide attempt. We will share our perspective on how other techniques excluding AI can help to alleviate this menace.AI based applications are playing a vital role to assist mental health. Our purpose is to study the role of AI in mental health.

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A Blueprint for an AI & AR-Based Eye Tracking System to Train Cardiology Professionals Better Interpret Electrocardiograms

Sqalli

Al-Thani

El‐Shazly

et al. 2022

Persuasive Technology

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Perspectives on Human-AI Interaction Applied to Health and Wellness Management: Between Milestones and Hurdles

Cited by 6 publications

References 26 publications

Navigating the Ethical Landscape: Implementing Machine Learning in Smart Healthcare Informatics

Navigating the Ethical Landscape: Implementing Machine Learning in Smart Healthcare Informatics

AI Based Assistance To Reduce Suicidal Tendency Among Youngsters

A Blueprint for an AI & AR-Based Eye Tracking System to Train Cardiology Professionals Better Interpret Electrocardiograms

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