AI Medical Compendium Topic:
Delivery of Health Care

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Right population, right resources, right algorithm: Using machine learning efficiently and effectively in surgical systems where data are a limited resource.

Surgery
There is a growing interest in using machine learning algorithms to support surgical care, diagnostics, and public health surveillance in low- and middle-income countries. From our own experience and the literature, we share several lessons for devel...

Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.

The American journal of bioethics : AJOB
The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders, such as depression, by using data from social media...

Role of the Health System in Combating Covid-19: Cross-Section Analysis and Artificial Neural Network Simulation for 124 Country Cases.

Social work in public health
In the fight against Covid-19, developed countries and developing countries diverge in success. This drew attention to the discussion of how different health systems and different levels of health spending are effective in combating Covid-19. In this...

For a critical appraisal of artificial intelligence in healthcare: The problem of bias in mHealth.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Artificial intelligence and big data are more and more used in medicine, either in prevention, diagnosis or treatment, and are clearly modifying the way medicine is thought and practiced. Some authors argue that the us...

How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.

Reviews in medical virology
The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent in...

Disruptive Innovation in Dentistry: What It Is and What Could Be Next.

Journal of dental research
Dentistry is a technically oriented profession, and the health care sector is significantly influenced by the ubiquitous trend of digitalization. Some of these digital developments have the potential to result in disruptive changes for dental practic...

The Emerging Hazard of AI-Related Health Care Discrimination.

The Hastings Center report
Artificial intelligence holds great promise for improved health-care outcomes. But it also poses substantial new hazards, including algorithmic discrimination. For example, an algorithm used to identify candidates for beneficial "high risk care manag...

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology
Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decisi...

Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders.

Healthcare management forum
Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intelligence (AI)-based imaging analytics are a promising healthcare innovation that aim to improve the ac...

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies.

Journal of biomedical informatics
Artificial intelligence (AI) has huge potential to improve the health and well-being of people, but adoption in clinical practice is still limited. Lack of transparency is identified as one of the main barriers to implementation, as clinicians should...